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Posted to commits@doris.apache.org by mo...@apache.org on 2019/09/02 01:06:40 UTC
[incubator-doris-website] branch asf-site updated: Add English
version of documents
This is an automated email from the ASF dual-hosted git repository.
morningman pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-doris-website.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 742996c Add English version of documents
742996c is described below
commit 742996ccbc5174febc0013d942001361365aadfe
Author: morningman <mo...@163.com>
AuthorDate: Mon Sep 2 09:06:19 2019 +0800
Add English version of documents
---
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.../Data Manipulation/SHOW EXPORT_EN.html | 285 +++
.../Data Manipulation/SHOW LOAD_EN.html | 295 +++
.../Data Manipulation/SHOW PARTITIONS_EN.html | 266 +++
.../Data Manipulation/SHOW PROPERTY_EN.html | 266 +++
.../Data Manipulation/SHOW REPOSITORIES_EN.html | 275 +++
.../Data Manipulation/SHOW RESTORE_EN.html | 293 +++
.../SHOW ROUTINE LOAD TASK_EN.html | 258 +++
.../Data Manipulation/SHOW ROUTINE LOAD_EN.html | 280 +++
.../Data Manipulation/SHOW SNAPSHOT_EN.html | 278 +++
.../Data Manipulation/SHOW TABLES_EN.html | 257 +++
.../Data Manipulation/SHOW TABLET_EN.html | 267 +++
.../Data Manipulation/STOP ROUTINE LOAD_EN.html | 258 +++
.../Data Manipulation/STREAM LOAD_EN.html | 323 +++
.../Data Manipulation/broker_load_EN.html | 575 ++++++
.../sql-statements/Data Manipulation/index.html | 405 ++++
.../Data Manipulation/insert_EN.html | 309 +++
.../sql-statements/Data Types/BIGINT_EN.html | 254 +++
.../sql-statements/Data Types/BOOLEAN_EN.html | 254 +++
.../sql-statements/Data Types/CHAR_EN.html | 254 +++
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.../sql-statements/Data Types/DATE_EN.html | 263 +++
.../sql-statements/Data Types/DECIMAL_EN.html | 255 +++
.../sql-statements/Data Types/DOUBLE_EN.html | 254 +++
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.../Data Types/HLL(HyperLogLog)_EN.html | 254 +++
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.../sql-statements/Data Types/TINYINT_EN.html | 254 +++
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.../sql-statements/Data Types/index.html | 299 +++
.../sql-statements/Utility/index.html | 255 +++
.../sql-statements/Utility/util_stmt_EN.html | 262 +++
.../en/sql-reference/sql-statements/index.html | 245 +++
content/genindex.html | 24 +-
content/index.html | 30 +-
content/nohup.out | Bin 1090 -> 1206995 bytes
content/objects.inv | Bin 4437 -> 8464 bytes
content/search.html | 24 +-
content/searchindex.js | 2 +-
1259 files changed, 172472 insertions(+), 81145 deletions(-)
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 1076f701508676587f586546f0b9ecda
+config: 8cb6a2384096d8de5f207439a086c90d
tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/content/Docs/cn/administrator-guide/alter-table/alter-table-rollup.html b/content/Docs/cn/administrator-guide/alter-table/alter-table-rollup.html
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-<li class="toctree-l4"><a class="reference internal" href="#id1">名词解释</a></li>
-<li class="toctree-l4"><a class="reference internal" href="#id2">原理介绍</a></li>
-<li class="toctree-l4"><a class="reference internal" href="#id3">创建作业</a></li>
-<li class="toctree-l4"><a class="reference internal" href="#id4">查看作业</a></li>
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- <div class="section" id="rollup">
-<h1>Rollup<a class="headerlink" href="#rollup" title="Permalink to this headline">¶</a></h1>
-<p>用户可以通过创建上卷表（Rollup）加速查询。关于 Rollup 的概念和使用方式可以参阅 <a class="reference internal" href="../../getting-started/data-model-rollup.html"><span class="doc">数据模型、ROLLUP 及前缀索引</span></a> 和 <a class="reference internal" href="../../getting-started/hit-the-rollup.html"><span class="doc">Rollup 与查询</span></a> 两篇文档。</p>
-<p>本文档主要介绍如何创建 Rollup 作业，以及创建 Rollup 的一些注意事项和常见问题。</p>
-<div class="section" id="id1">
-<h2>名词解释<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>Base Table：基表。每一个表被创建时，都对应一个基表。基表存储了这个表的完整的数据。Rollup 通常基于基表中的数据创建（也可以通过其他 Rollup 创建）。</li>
-<li>Index：物化索引。Rollup 或 Base Table 都被称为物化索引。</li>
-<li>Transaction：事务。每一个导入任务都是一个事务，每个事务有一个唯一递增的 Transaction ID。</li>
-</ul>
-</div>
-<div class="section" id="id2">
-<h2>原理介绍<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<p>创建 Rollup 的基本过程，是通过 Base 表的数据，生成一份新的包含指定列的 Rollup 的数据。其中主要需要进行两部分数据转换，一是已存在的历史数据的转换，二是在 Rollup 执行过程中，新到达的导入数据的转换。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+----------+</span>
-<span class="o">|</span> <span class="n">Load</span> <span class="n">Job</span> <span class="o">|</span>
-<span class="o">+----+-----+</span>
- <span class="o">|</span>
- <span class="o">|</span> <span class="n">Load</span> <span class="n">job</span> <span class="n">generates</span> <span class="n">both</span> <span class="n">base</span> <span class="ow">and</span> <span class="n">rollup</span> <span class="n">index</span> <span class="n">data</span>
- <span class="o">|</span>
- <span class="o">|</span> <span class="o">+------------------+</span> <span class="o">+---------------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">Base</span> <span class="n">Index</span> <span class="o">|</span> <span class="o">|</span> <span class="n">Base</span> <span class="n">Index</span> <span class="o">|</span>
- <span class="o">+------></span> <span class="n">New</span> <span class="n">Incoming</span> <span class="n">Data</span><span class="o">|</span> <span class="o">|</span> <span class="n">History</span> <span class="n">Data</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">+------------------+</span> <span class="o">+------+--------+</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">Convert</span> <span class="n">history</span> <span class="n">data</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">+------------------+</span> <span class="o">+------</span><span class="n">v</span><span class="o">--------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">Rollup</span> <span class="n">Index</span> <span class="o">|</span> <span class="o">|</span> <span class="n">Rollup</span> <span class="n">Index</span> <span class="o">|</span>
- <span class="o">+------></span> <span class="n">New</span> <span class="n">Incoming</span> <span class="n">Data</span><span class="o">|</span> <span class="o">|</span> <span class="n">History</span> <span class="n">Data</span> <span class="o">|</span>
- <span class="o">+------------------+</span> <span class="o">+---------------+</span>
-</pre></div>
-</div>
-<p>在开始转换历史数据之前，Doris 会获取一个最新的 Transaction ID。并等待这个 Transaction ID 之前的所有导入事务完成。这个 Transaction ID 成为分水岭。意思是，Doris 保证在分水岭之后的所有导入任务，都会同时为 Rollup Index 生成数据。这样当历史数据转换完成后，可以保证 Rollup 和 Base 表的数据是齐平的。</p>
-</div>
-<div class="section" id="id3">
-<h2>创建作业<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>创建 Rollup 的具体语法可以查看帮助 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span></code> 中 Rollup 部分的说明。</p>
-<p>Rollup 的创建是一个异步过程，作业提交成功后，用户需要通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">ROLLUP</span></code> 命令来查看作业进度。</p>
-</div>
-<div class="section" id="id4">
-<h2>查看作业<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">ROLLUP</span></code> 可以查看当前正在执行或已经完成的 Rollup 作业。举例如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">JobId</span><span class="p">:</span> <span class="mi">20037</span>
- <span class="n">TableName</span><span class="p">:</span> <span class="n">tbl1</span>
- <span class="n">CreateTime</span><span class="p">:</span> <span class="mi">2019</span><span class="o">-</span><span class="mi">08</span><span class="o">-</span><span class="mi">06</span> <span class="mi">15</span><span class="p">:</span><span class="mi">38</span><span class="p">:</span><span class="mi">49</span>
- <span class="n">FinishedTime</span><span class="p">:</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span>
- <span class="n">BaseIndexName</span><span class="p">:</span> <span class="n">tbl1</span>
-<span class="n">RollupIndexName</span><span class="p">:</span> <span class="n">r1</span>
- <span class="n">RollupId</span><span class="p">:</span> <span class="mi">20038</span>
- <span class="n">TransactionId</span><span class="p">:</span> <span class="mi">10034</span>
- <span class="n">State</span><span class="p">:</span> <span class="n">PENDING</span>
- <span class="n">Msg</span><span class="p">:</span>
- <span class="n">Progress</span><span class="p">:</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span>
- <span class="n">Timeout</span><span class="p">:</span> <span class="mi">86400</span>
-</pre></div>
-</div>
-<ul class="simple">
-<li>JobId：每个 Rollup 作业的唯一 ID。</li>
-<li>TableName：Rollup 对应的基表的表名。</li>
-<li>CreateTime：作业创建时间。</li>
-<li>FinishedTime：作业结束时间。如未结束，则显示 “N/A”。</li>
-<li>BaseIndexName：Rollup 对应的源 Index 的名称。</li>
-<li>RollupIndexName：Rollup 的名称。</li>
-<li>RollupId：Rollup 的唯一 ID。</li>
-<li>TransactionId：转换历史数据的分水岭 transaction ID。</li>
-<li>State：作业所在阶段。<ul>
-<li>PENDING：作业在队列中等待被调度。</li>
-<li>WAITING_TXN：等待分水岭 transaction ID 之前的导入任务完成。</li>
-<li>RUNNING：历史数据转换中。</li>
-<li>FINISHED：作业成功。</li>
-<li>CANCELLED：作业失败。</li>
-</ul>
-</li>
-<li>Msg：如果作业失败，这里会显示失败信息。</li>
-<li>Progress：作业进度。只有在 RUNNING 状态才会显示进度。进度是以 M/N 的形式显示。其中 N 为 Rollup 的总副本数。M 为已完成历史数据转换的副本数。</li>
-<li>Timeout：作业超时时间。单位秒。</li>
-</ul>
-</div>
-<div class="section" id="id5">
-<h2>取消作业<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h2>
-<p>在作业状态不为 FINISHED 或 CANCELLED 的情况下，可以通过以下命令取消 Rollup 作业：</p>
-<p><code class="docutils literal notranslate"><span class="pre">CANCEL</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">ROLLUP</span> <span class="pre">FROM</span> <span class="pre">tbl_name;</span></code></p>
-</div>
-<div class="section" id="id6">
-<h2>注意事项<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">一张表在同一时间只能有一个 Rollup 作业在运行。且一个作业中只能创建一个 Rollup。</p>
-</li>
-<li><p class="first">Rollup 操作不阻塞导入和查询操作。</p>
-</li>
-<li><p class="first">如果 DELETE 操作，where 条件中的某个 Key 列在某个 Rollup 中不存在，则不允许该 DELETE。</p>
-<p>如果某个 Key 列在某一 Rollup 中不存在，则 DELETE 操作无法对该 Rollup 进行数据删除，从而无法保证 Rollup 表和 Base 表的数据一致性。</p>
-</li>
-<li><p class="first">Rollup 的列必须存在于 Base 表中。</p>
-<p>Rollup 的列永远是 Base 表列的子集。不能出现 Base 表中不存在的列。</p>
-</li>
-<li><p class="first">如果 Rollup 中包含 REPLACE 聚合类型的列，则该 Rollup 必须包含所有 Key 列。</p>
-<p>假设 Base 表结构如下：</p>
-<p><code class="docutils literal notranslate"><span class="pre">(k1</span> <span class="pre">INT,</span> <span class="pre">k2</span> <span class="pre">INT,</span> <span class="pre">v1</span> <span class="pre">INT</span> <span class="pre">REPLACE,</span> <span class="pre">v2</span> <span class="pre">INT</span> <span class="pre">SUM)</span></code></p>
-<p>如果需要创建的 Rollup 包含 <code class="docutils literal notranslate"><span class="pre">v1</span></code> 列，则必须包含 <code class="docutils literal notranslate"><span class="pre">k1</span></code>, <code class="docutils literal notranslate"><span class="pre">k2</span></code> 列。否则系统无法决定 <code class="docutils literal notranslate"><span class="pre">v1</span></code> 列在 Rollup 中的取值。</p>
-<p>注意，Unique 数据模型表中的所有 Value 列都是 REPLACE 聚合类型。</p>
-</li>
-<li><p class="first">DUPLICATE 数据模型表的 Rollup，可以指定 Rollup 的 DUPLICATE KEY。</p>
-<p>DUPLICATE 数据模型表中的 DUPLICATE KEY 其实就是排序列。Rollup 可以指定自己的排序列，但排序列必须是 Rollup 列顺序的前缀。如果不指定，则系统会检查 Rollup 是否包含了 Base 表的所有排序列，如果没有包含，则会报错。举例：</p>
-<p>Base 表结构：<code class="docutils literal notranslate"><span class="pre">(k1</span> <span class="pre">INT,</span> <span class="pre">k2</span> <span class="pre">INT,</span> <span class="pre">k3</span> <span class="pre">INT)</span> <span class="pre">DUPLICATE</span> <span class="pre">KEY(k1,</span> <span class="pre">k2)</span></code></p>
-<p>则 Rollup 可以为：<code class="docutils literal notranslate"><span class="pre">(k2</span> <span class="pre">INT,</span> <span class="pre">k1</span> <span class="pre">INT)</span> <span class="pre">DUPLICATE</span> <span class="pre">KEY(k2)</span></code></p>
-</li>
-<li><p class="first">Rollup 不需要包含 Base 表的分区列或分桶列。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id7">
-<h2>常见问题<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">一个表可以创建多少 Rollup</p>
-<p>一个表能够创建的 Rollup 个数理论上没有限制，但是过多的 Rollup 会影响导入性能。因为导入时，会同时给所有 Rollup 产生数据。同时 Rollup 会占用物理存储空间。通常一个表的 Rollup 数量在 10 个以内比较合适。</p>
-</li>
-<li><p class="first">Rollup 创建的速度</p>
-<p>目前 Rollup 创建速度按照最差效率估计约为 10MB/s。保守起见，用户可以根据这个速率来设置作业的超时时间。</p>
-</li>
-<li><p class="first">提交作业报错 <code class="docutils literal notranslate"><span class="pre">Table</span> <span class="pre">xxx</span> <span class="pre">is</span> <span class="pre">not</span> <span class="pre">stable.</span> <span class="pre">...</span></code></p>
-<p>Rollup 只有在表数据完整且非均衡状态下才可以开始。如果表的某些数据分片副本不完整，或者某些副本正在进行均衡操作，则提交会被拒绝。</p>
-<p>数据分片副本是否完整，可以通过以下命令查看：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ADMIN</span> <span class="pre">SHOW</span> <span class="pre">REPLICA</span> <span class="pre">STATUS</span> <span class="pre">FROM</span> <span class="pre">tbl</span> <span class="pre">WHERE</span> <span class="pre">STATUS</span> <span class="pre">!=</span> <span class="pre">"OK";</span></code></p>
-<p>如果有返回结果，则说明有副本有问题。通常系统会自动修复这些问题，用户也可以通过以下命令优先修复这个表：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ADMIN</span> <span class="pre">REPAIR</span> <span class="pre">TABLE</span> <span class="pre">tbl1;</span></code></p>
-<p>用户可以通过以下命令查看是否有正在运行的均衡任务：</p>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">PROC</span> <span class="pre">"/cluster_balance/pending_tablets";</span></code></p>
-<p>可以等待均衡任务完成，或者通过以下命令临时禁止均衡操作：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ADMIN</span> <span class="pre">SET</span> <span class="pre">FRONTEND</span> <span class="pre">CONFIG</span> <span class="pre">("disable_balance"</span> <span class="pre">=</span> <span class="pre">"true");</span></code></p>
-</li>
-</ul>
-</div>
-<div class="section" id="id8">
-<h2>相关配置<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE 配置<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li><code class="docutils literal notranslate"><span class="pre">alter_table_timeout_second</span></code>：作业默认超时时间，86400 秒。</li>
-</ul>
-</div>
-<div class="section" id="be">
-<h3>BE 配置<a class="headerlink" href="#be" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li><code class="docutils literal notranslate"><span class="pre">alter_tablet_worker_count</span></code>：在 BE 端用于执行历史数据转换的线程数。默认为 3。如果希望加快 Rollup 作业的速度，可以适当调大这个参数后重启 BE。但过多的转换线程可能会导致 IO 压力增加，影响其他操作。该线程和 Schema Change 作业共用。</li>
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- <div class="section" id="scheam-change">
-<h1>Scheam Change<a class="headerlink" href="#scheam-change" title="Permalink to this headline">¶</a></h1>
-<p>用户可以通过 Scheam Change 操作来修改已存在表的 Schema。目前 Doris 支持以下几种修改:</p>
-<ul class="simple">
-<li>增加、删除列</li>
-<li>修改列类型</li>
-<li>调整列顺序</li>
-<li>增加、修改 Bloom Filter</li>
-</ul>
-<p>本文档主要介绍如何创建 Scheam Change 作业，以及进行 Scheam Change 的一些注意事项和常见问题。</p>
-<div class="section" id="id1">
-<h2>名词解释<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>Base Table：基表。每一个表被创建时，都对应一个基表。</li>
-<li>Rollup：基于基表或者其他 Rollup 创建出来的上卷表。</li>
-<li>Index：物化索引。Rollup 或 Base Table 都被称为物化索引。</li>
-<li>Transaction：事务。每一个导入任务都是一个事务，每个事务有一个唯一递增的 Transaction ID。</li>
-</ul>
-</div>
-<div class="section" id="id2">
-<h2>原理介绍<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<p>执行 Schema Change 的基本过程，是通过原 Index 的数据，生成一份新 Schema 的 Index 的数据。其中主要需要进行两部分数据转换，一是已存在的历史数据的转换，二是在 Schema Change 执行过程中，新到达的导入数据的转换。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+----------+</span>
-<span class="o">|</span> <span class="n">Load</span> <span class="n">Job</span> <span class="o">|</span>
-<span class="o">+----+-----+</span>
- <span class="o">|</span>
- <span class="o">|</span> <span class="n">Load</span> <span class="n">job</span> <span class="n">generates</span> <span class="n">both</span> <span class="n">origin</span> <span class="ow">and</span> <span class="n">new</span> <span class="n">index</span> <span class="n">data</span>
- <span class="o">|</span>
- <span class="o">|</span> <span class="o">+------------------+</span> <span class="o">+---------------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">Origin</span> <span class="n">Index</span> <span class="o">|</span> <span class="o">|</span> <span class="n">Origin</span> <span class="n">Index</span> <span class="o">|</span>
- <span class="o">+------></span> <span class="n">New</span> <span class="n">Incoming</span> <span class="n">Data</span><span class="o">|</span> <span class="o">|</span> <span class="n">History</span> <span class="n">Data</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">+------------------+</span> <span class="o">+------+--------+</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">Convert</span> <span class="n">history</span> <span class="n">data</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">+------------------+</span> <span class="o">+------</span><span class="n">v</span><span class="o">--------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">New</span> <span class="n">Index</span> <span class="o">|</span> <span class="o">|</span> <span class="n">New</span> <span class="n">Index</span> <span class="o">|</span>
- <span class="o">+------></span> <span class="n">New</span> <span class="n">Incoming</span> <span class="n">Data</span><span class="o">|</span> <span class="o">|</span> <span class="n">History</span> <span class="n">Data</span> <span class="o">|</span>
- <span class="o">+------------------+</span> <span class="o">+---------------+</span>
-</pre></div>
-</div>
-<p>在开始转换历史数据之前，Doris 会获取一个最新的 Transaction ID。并等待这个 Transaction ID 之前的所有导入事务完成。这个 Transaction ID 成为分水岭。意思是，Doris 保证在分水岭之后的所有导入任务，都会同时为原 Index 和新 Index 生成数据。这样当历史数据转换完成后，可以保证新的 Index 中的数据是完整的。</p>
-</div>
-<div class="section" id="id3">
-<h2>创建作业<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>创建 Scheam Change 的具体语法可以查看帮助 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span></code> 中 Scheam Change 部分的说明。</p>
-<p>Scheam Change 的创建是一个异步过程，作业提交成功后，用户需要通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">COLUMN</span></code> 命令来查看作业进度。</p>
-</div>
-<div class="section" id="id4">
-<h2>查看作业<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">COLUMN</span></code> 可以查看当前正在执行或已经完成的 Schema Change 作业。当一次 Schema Change 作业涉及到多个 Index 时，该命令会显示多行，每行对应一个 Index。举例如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">JobId</span><span class="p">:</span> <span class="mi">20021</span>
- <span class="n">TableName</span><span class="p">:</span> <span class="n">tbl1</span>
- <span class="n">CreateTime</span><span class="p">:</span> <span class="mi">2019</span><span class="o">-</span><span class="mi">08</span><span class="o">-</span><span class="mi">05</span> <span class="mi">23</span><span class="p">:</span><span class="mi">03</span><span class="p">:</span><span class="mi">13</span>
- <span class="n">FinishTime</span><span class="p">:</span> <span class="mi">2019</span><span class="o">-</span><span class="mi">08</span><span class="o">-</span><span class="mi">05</span> <span class="mi">23</span><span class="p">:</span><span class="mi">03</span><span class="p">:</span><span class="mi">42</span>
- <span class="n">IndexName</span><span class="p">:</span> <span class="n">tbl1</span>
- <span class="n">IndexId</span><span class="p">:</span> <span class="mi">20022</span>
-<span class="n">OriginIndexId</span><span class="p">:</span> <span class="mi">20017</span>
-<span class="n">SchemaVersion</span><span class="p">:</span> <span class="mi">2</span><span class="p">:</span><span class="mi">792557838</span>
-<span class="n">TransactionId</span><span class="p">:</span> <span class="mi">10023</span>
- <span class="n">State</span><span class="p">:</span> <span class="n">FINISHED</span>
- <span class="n">Msg</span><span class="p">:</span>
- <span class="n">Progress</span><span class="p">:</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span>
- <span class="n">Timeout</span><span class="p">:</span> <span class="mi">86400</span>
-</pre></div>
-</div>
-<ul class="simple">
-<li>JobId：每个 Schema Change 作业的唯一 ID。</li>
-<li>TableName：Schema Change 对应的基表的表名。</li>
-<li>CreateTime：作业创建时间。</li>
-<li>FinishedTime：作业结束时间。如未结束，则显示 “N/A”。</li>
-<li>IndexName： 本次修改所涉及的某一个 Index 的名称。</li>
-<li>IndexId：新的 Index 的唯一 ID。</li>
-<li>OriginIndexId：旧的 Index 的唯一 ID。</li>
-<li>SchemaVersion：以 M:N 的格式展示。其中 M 表示本次 Schema Change 变更的版本，N 表示对应的 Hash 值。每次 Schema Change，版本都会递增。</li>
-<li>TransactionId：转换历史数据的分水岭 transaction ID。</li>
-<li>State：作业所在阶段。<ul>
-<li>PENDING：作业在队列中等待被调度。</li>
-<li>WAITING_TXN：等待分水岭 transaction ID 之前的导入任务完成。</li>
-<li>RUNNING：历史数据转换中。</li>
-<li>FINISHED：作业成功。</li>
-<li>CANCELLED：作业失败。</li>
-</ul>
-</li>
-<li>Msg：如果作业失败，这里会显示失败信息。</li>
-<li>Progress：作业进度。只有在 RUNNING 状态才会显示进度。进度是以 M/N 的形式显示。其中 N 为 Schema Change 涉及的总副本数。M 为已完成历史数据转换的副本数。</li>
-<li>Timeout：作业超时时间。单位秒。</li>
-</ul>
-</div>
-<div class="section" id="id5">
-<h2>取消作业<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h2>
-<p>在作业状态不为 FINISHED 或 CANCELLED 的情况下，可以通过以下命令取消 Schema Change 作业：</p>
-<p><code class="docutils literal notranslate"><span class="pre">CANCEL</span> <span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">COLUMN</span> <span class="pre">FROM</span> <span class="pre">tbl_name;</span></code></p>
-</div>
-<div class="section" id="id6">
-<h2>最佳实践<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<p>Schema Change 可以在一个作业中，对多个 Index 进行不同的修改。举例如下：</p>
-<p>源 Schema：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+-----------+-------+------+------+------+---------+-------+</span>
-<span class="o">|</span> <span class="n">IndexName</span> <span class="o">|</span> <span class="n">Field</span> <span class="o">|</span> <span class="n">Type</span> <span class="o">|</span> <span class="n">Null</span> <span class="o">|</span> <span class="n">Key</span> <span class="o">|</span> <span class="n">Default</span> <span class="o">|</span> <span class="n">Extra</span> <span class="o">|</span>
-<span class="o">+-----------+-------+------+------+------+---------+-------+</span>
-<span class="o">|</span> <span class="n">tbl1</span> <span class="o">|</span> <span class="n">k1</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k2</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k3</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">rollup2</span> <span class="o">|</span> <span class="n">k2</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">rollup1</span> <span class="o">|</span> <span class="n">k1</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k2</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+-----------+-------+------+------+------+---------+-------+</span>
-</pre></div>
-</div>
-<p>可以通过以下命令给 rollup1 和 rollup2 都加入一列 k4，并且再给 rollup2 加入一列 k5：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">ALTER</span> <span class="n">TABLE</span> <span class="n">tbl1</span>
-<span class="n">ADD</span> <span class="n">COLUMN</span> <span class="n">k4</span> <span class="n">INT</span> <span class="n">default</span> <span class="s2">"1"</span> <span class="n">to</span> <span class="n">rollup1</span><span class="p">,</span>
-<span class="n">ADD</span> <span class="n">COLUMN</span> <span class="n">k4</span> <span class="n">INT</span> <span class="n">default</span> <span class="s2">"1"</span> <span class="n">to</span> <span class="n">rollup2</span><span class="p">,</span>
-<span class="n">ADD</span> <span class="n">COLUMN</span> <span class="n">k5</span> <span class="n">INT</span> <span class="n">default</span> <span class="s2">"1"</span> <span class="n">to</span> <span class="n">rollup2</span><span class="p">;</span>
-</pre></div>
-</div>
-<p>完成后，Schema 变为：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+-----------+-------+------+------+------+---------+-------+</span>
-<span class="o">|</span> <span class="n">IndexName</span> <span class="o">|</span> <span class="n">Field</span> <span class="o">|</span> <span class="n">Type</span> <span class="o">|</span> <span class="n">Null</span> <span class="o">|</span> <span class="n">Key</span> <span class="o">|</span> <span class="n">Default</span> <span class="o">|</span> <span class="n">Extra</span> <span class="o">|</span>
-<span class="o">+-----------+-------+------+------+------+---------+-------+</span>
-<span class="o">|</span> <span class="n">tbl1</span> <span class="o">|</span> <span class="n">k1</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k2</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k3</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k4</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k5</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">rollup2</span> <span class="o">|</span> <span class="n">k2</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k4</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k5</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">rollup1</span> <span class="o">|</span> <span class="n">k1</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k2</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">k4</span> <span class="o">|</span> <span class="n">INT</span> <span class="o">|</span> <span class="n">No</span> <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+-----------+-------+------+------+------+---------+-------+</span>
-</pre></div>
-</div>
-<p>可以看到，Base 表 tbl1 也自动加入了 k4, k5 列。即给任意 rollup 增加的列，都会自动加入到 Base 表中。</p>
-<p>同时，不允许向 Rollup 中加入 Base 表已经存在的列。如果用户需要这样做，可以重新建立一个包含新增列的 Rollup，之后在删除原 Rollup。</p>
-</div>
-<div class="section" id="id7">
-<h2>注意事项<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">一张表在同一时间只能有一个 Schema Change 作业在运行。</p>
-</li>
-<li><p class="first">Schema Change 操作不阻塞导入和查询操作。</p>
-</li>
-<li><p class="first">分区列和分桶列不能修改。</p>
-</li>
-<li><p class="first">如果 Schema 中有 REPLACE 方式聚合的 value 列，则不允许删除 Key 列。</p>
-<p>如果删除 Key 列，Doris 无法决定 REPLACE 列的取值。</p>
-<p>Unique 数据模型表的所有非 Key 列都是 REPLACE 聚合方式。</p>
-</li>
-<li><p class="first">在新增聚合类型为 SUM 或者 REPLACE 的 value 列时，该列的默认值对历史数据没有含义。</p>
-<p>因为历史数据已经失去明细信息，所以默认值的取值并不能实际反映聚合后的取值。</p>
-</li>
-<li><p class="first">当修改列类型时，除 Type 以外的字段都需要按原列上的信息补全。</p>
-<p>如修改列 <code class="docutils literal notranslate"><span class="pre">k1</span> <span class="pre">INT</span> <span class="pre">SUM</span> <span class="pre">NULL</span> <span class="pre">DEFAULT</span> <span class="pre">"1"</span></code> 类型为 BIGINT，则需执行命令如下：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">tbl1</span> <span class="pre">MODIFY</span> <span class="pre">COLUMN</span> <span class="pre">`k1</span> <span class="pre">BIGINT</span> <span class="pre">SUM</span> <span class="pre">NULL</span> <span class="pre">DEFAULT</span> <span class="pre">"1";</span></code></p>
-<p>注意，除新的列类型外，如聚合方式，Nullable 属性，以及默认值都要按照原信息补全。</p>
-</li>
-<li><p class="first">不支持修改列名称、聚合类型、Nullable 属性、默认值以及列注释。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id8">
-<h2>常见问题<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">Schema Change 的执行速度</p>
-<p>目前 Schema Change 执行速度按照最差效率估计约为 10MB/s。保守起见，用户可以根据这个速率来设置作业的超时时间。</p>
-</li>
-<li><p class="first">提交作业报错 <code class="docutils literal notranslate"><span class="pre">Table</span> <span class="pre">xxx</span> <span class="pre">is</span> <span class="pre">not</span> <span class="pre">stable.</span> <span class="pre">...</span></code></p>
-<p>Schema Change 只有在表数据完整且非均衡状态下才可以开始。如果表的某些数据分片副本不完整，或者某些副本正在进行均衡操作，则提交会被拒绝。</p>
-<p>数据分片副本是否完整，可以通过以下命令查看：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ADMIN</span> <span class="pre">SHOW</span> <span class="pre">REPLICA</span> <span class="pre">STATUS</span> <span class="pre">FROM</span> <span class="pre">tbl</span> <span class="pre">WHERE</span> <span class="pre">STATUS</span> <span class="pre">!=</span> <span class="pre">"OK";</span></code></p>
-<p>如果有返回结果，则说明有副本有问题。通常系统会自动修复这些问题，用户也可以通过以下命令优先修复这个表：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ADMIN</span> <span class="pre">REPAIR</span> <span class="pre">TABLE</span> <span class="pre">tbl1;</span></code></p>
-<p>用户可以通过以下命令查看是否有正在运行的均衡任务：</p>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">PROC</span> <span class="pre">"/cluster_balance/pending_tablets";</span></code></p>
-<p>可以等待均衡任务完成，或者通过以下命令临时禁止均衡操作：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ADMIN</span> <span class="pre">SET</span> <span class="pre">FRONTEND</span> <span class="pre">CONFIG</span> <span class="pre">("disable_balance"</span> <span class="pre">=</span> <span class="pre">"true");</span></code></p>
-</li>
-</ul>
-</div>
-<div class="section" id="id9">
-<h2>相关配置<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE 配置<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li><code class="docutils literal notranslate"><span class="pre">alter_table_timeout_second</span></code>：作业默认超时时间，86400 秒。</li>
-</ul>
-</div>
-<div class="section" id="be">
-<h3>BE 配置<a class="headerlink" href="#be" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li><code class="docutils literal notranslate"><span class="pre">alter_tablet_worker_count</span></code>：在 BE 端用于执行历史数据转换的线程数。默认为 3。如果希望加快 Schema Change 作业的速度，可以适当调大这个参数后重启 BE。但过多的转换线程可能会导致 IO 压力增加，影响其他操作。该线程和 Rollup 作业共用。</li>
-</ul>
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-<h1>备份与恢复<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h1>
-<p>Doris 支持将当前数据以文件的形式，通过 broker 备份到远端存储系统中。之后可以通过 恢复 命令，从远端存储系统中将数据恢复到任意 Doris 集群。通过这个功能，Doris 可以支持将数据定期的进行快照备份。也可以通过这个功能，在不同集群间进行数据迁移。</p>
-<p>该功能需要 Doris 版本 0.8.2+</p>
-<p>使用该功能，需要部署对应远端存储的 broker。如 BOS、HDFS 等。可以通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">BROKER;</span></code> 查看当前部署的 broker。</p>
-<div class="section" id="id2">
-<h2>简要原理说明<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="backup">
-<h3>备份（Backup）<a class="headerlink" href="#backup" title="Permalink to this headline">¶</a></h3>
-<p>备份操作是将指定表或分区的数据，直接以 Doris 存储的文件的形式，上传到远端仓库中进行存储。当用户提交 Backup 请求后，系统内部会做如下操作：</p>
-<ol>
-<li><p class="first">快照及快照上传</p>
-<p>快照阶段会对指定的表或分区数据文件进行快照。之后，备份都是对快照进行操作。在快照之后，对表进行的更改、导入等操作都不再影响备份的结果。快照只是对当前数据文件产生一个硬链，耗时很少。快照完成后，会开始对这些快照文件进行逐一上传。快照上传由各个 Backend 并发完成。</p>
-</li>
-<li><p class="first">元数据准备及上传</p>
-<p>数据文件快照上传完成后，Frontend 会首先将对应元数据写成本地文件，然后通过 broker 将本地元数据文件上传到远端仓库。完成最终备份作业。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="restore">
-<h3>恢复（Restore）<a class="headerlink" href="#restore" title="Permalink to this headline">¶</a></h3>
-<p>恢复操作需要指定一个远端仓库中已存在的备份，然后将这个备份的内容恢复到本地集群中。当用户提交 Restore 请求后，系统内部会做如下操作：</p>
-<ol>
-<li><p class="first">在本地创建对应的元数据</p>
-<p>这一步首先会在本地集群中，创建恢复对应的表分区等结构。创建完成后，该表可见，但是不可访问。</p>
-</li>
-<li><p class="first">本地snapshot</p>
-<p>这一步是将上一步创建的表做一个快照。这其实是一个空快照（因为刚创建的表是没有数据的），其目的主要是在 Backend 上产生对应的快照目录，用于之后接收从远端仓库下载的快照文件。</p>
-</li>
-<li><p class="first">下载快照</p>
-<p>远端仓库中的快照文件，会被下载到对应的上一步生成的快照目录中。这一步由各个 Backend 并发完成。</p>
-</li>
-<li><p class="first">生效快照</p>
-<p>快照下载完成后，我们要将各个快照映射为当前本地表的元数据。然后重新加载这些快照，使之生效，完成最终的恢复作业。</p>
-</li>
-</ol>
-</div>
-</div>
-<div class="section" id="id3">
-<h2>最佳实践<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id4">
-<h3>备份<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h3>
-<p>当前我们支持最小分区（Partition）粒度的全量备份（增量备份有可能在未来版本支持）。如果需要对数据进行定期备份，首先需要在建表时，合理的规划表的分区及分桶，比如按时间进行分区。然后在之后的运行过程中，按照分区粒度进行定期的数据备份。</p>
-</div>
-<div class="section" id="id5">
-<h3>数据迁移<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<p>用户可以先将数据备份到远端仓库，再通过远端仓库将数据恢复到另一个集群，完成数据迁移。因为数据备份是通过快照的形式完成的，所以，在备份作业的快照阶段之后的新的导入数据，是不会备份的。因此，在快照完成后，到恢复作业完成这期间，在原集群上导入的数据，都需要在新集群上同样导入一遍。</p>
-<p>建议在迁移完成后，对新旧两个集群并行导入一段时间。完成数据和业务正确性校验后，再将业务迁移到新的集群。</p>
-</div>
-</div>
-<div class="section" id="id6">
-<h2>重点说明<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<ol class="simple">
-<li>备份恢复相关的操作目前只允许拥有 ADMIN 权限的用户执行。</li>
-<li>一个 Database 内，只允许有一个正在执行的备份或恢复作业。</li>
-<li>备份和恢复都支持最小分区（Partition）级别的操作，当表的数据量很大时，建议按分区分别执行，以降低失败重试的代价。</li>
-<li>因为备份恢复操作，操作的都是实际的数据文件。所以当一个表的分片过多，或者一个分片有过多的小版本时，可能即使总数据量很小，依然需要备份或恢复很长时间。用户可以通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">PARTITIONS</span> <span class="pre">FROM</span> <span class="pre">table_name;</span></code> 和 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">TABLET</span> <span class="pre">FROM</span> <span class="pre">table_name;</span></code> 来查看各个分区的分片数量，以及各个分片的文件版本数量，来预估作业执行时间。文件数量对作 [...]
-<li>当通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">BACKUP</span></code> 或者 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">RESTORE</span></code> 命令查看作业状态时。有可能会在 <code class="docutils literal notranslate"><span class="pre">TaskErrMsg</span></code> 一列中看到错误信息。但只要 <code class="docutils literal notranslate"><span class="pre">State</span></code> 列不为
-<code class="docutils literal notranslate"><span class="pre">CANCELLED</span></code>，则说明作业依然在继续。这些 Task 有可能会重试成功。当然，有些 Task 错误，也会直接导致作业失败。</li>
-<li>如果恢复作业是一次覆盖操作（指定恢复数据到已经存在的表或分区中），那么从恢复作业的 <code class="docutils literal notranslate"><span class="pre">COMMIT</span></code> 阶段开始，当前集群上被覆盖的数据有可能不能再被还原。此时如果恢复作业失败或被取消，有可能造成之前的数据已损坏且无法访问。这种情况下，只能通过再次执行恢复操作，并等待作业完成。因此，我们建议，如无必要，尽量不要使用覆盖的方式恢复数据，除非确认当前数据已不再使用。</li>
-</ol>
-</div>
-<div class="section" id="id7">
-<h2>相关命令<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
-<p>和备份恢复功能相关的命令如下。以下命令，都可以通过 mysql-client 连接 Doris 后，使用 <code class="docutils literal notranslate"><span class="pre">help</span> <span class="pre">cmd;</span></code> 的方式查看详细帮助。</p>
-<ol>
-<li><p class="first">CREATE REPOSITORY</p>
-<p>创建一个远端仓库路径，用于备份或恢复。</p>
-</li>
-<li><p class="first">BACKUP</p>
-<p>执行一次备份操作。</p>
-</li>
-<li><p class="first">SHOW BACKUP</p>
-<p>查看最近一次 backup 作业的执行情况，包括：</p>
-<ul class="simple">
-<li>JobId：本次备份作业的 id。</li>
-<li>SnapshotName：用户指定的本次备份作业的名称（Label）。</li>
-<li>DbName：备份作业对应的 Database。</li>
-<li>State：备份作业当前所在阶段：<ul>
-<li>PENDING：作业初始状态。</li>
-<li>SNAPSHOTING：正在进行快照操作。</li>
-<li>UPLOAD_SNAPSHOT：快照结束，准备上传。</li>
-<li>UPLOADING：正在上传快照。</li>
-<li>SAVE_META：正在本地生成元数据文件。</li>
-<li>UPLOAD_INFO：上传元数据文件和本次备份作业的信息。</li>
-<li>FINISHED：备份完成。</li>
-<li>CANCELLED：备份失败或被取消。</li>
-</ul>
-</li>
-<li>BackupObjs：本次备份涉及的表和分区的清单。</li>
-<li>CreateTime：作业创建时间。</li>
-<li>SnapshotFinishedTime：快照完成时间。</li>
-<li>UploadFinishedTime：快照上传完成时间。</li>
-<li>FinishedTime：本次作业完成时间。</li>
-<li>UnfinishedTasks：在 <code class="docutils literal notranslate"><span class="pre">SNAPSHOTTING</span></code>，<code class="docutils literal notranslate"><span class="pre">UPLOADING</span></code> 等阶段，会有多个子任务在同时进行，这里展示的当前阶段，未完成的子任务的 task id。</li>
-<li>TaskErrMsg：如果有子任务执行出错，这里会显示对应子任务的错误信息。</li>
-<li>Status：用于记录在整个作业过程中，可能出现的一些状态信息。</li>
-<li>Timeout：作业的超时时间，单位是秒。</li>
-</ul>
-</li>
-<li><p class="first">SHOW SNAPSHOT</p>
-<p>查看远端仓库中已存在的备份。</p>
-<ul class="simple">
-<li>Snapshot：备份时指定的该备份的名称（Label）。</li>
-<li>Timestamp：备份的时间戳。</li>
-<li>Status：该备份是否正常。</li>
-</ul>
-<p>如果在 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">SNAPSHOT</span></code> 后指定了 where 子句，则可以显示更详细的备份信息。</p>
-<ul class="simple">
-<li>Database：备份时对应的 Database。</li>
-<li>Details：展示了该备份完整的数据目录结构。</li>
-</ul>
-</li>
-<li><p class="first">RESTORE</p>
-<p>执行一次恢复操作。</p>
-</li>
-<li><p class="first">SHOW RESTORE</p>
-<p>查看最近一次 restore 作业的执行情况，包括：</p>
-<ul class="simple">
-<li>JobId：本次恢复作业的 id。</li>
-<li>Label：用户指定的仓库中备份的名称（Label）。</li>
-<li>Timestamp：用户指定的仓库中备份的时间戳。</li>
-<li>DbName：恢复作业对应的 Database。</li>
-<li>State：恢复作业当前所在阶段：<ul>
-<li>PENDING：作业初始状态。</li>
-<li>SNAPSHOTING：正在进行本地新建表的快照操作。</li>
-<li>DOWNLOAD：正在发送下载快照任务。</li>
-<li>DOWNLOADING：快照正在下载。</li>
-<li>COMMIT：准备生效已下载的快照。</li>
-<li>COMMITTING：正在生效已下载的快照。</li>
-<li>FINISHED：恢复完成。</li>
-<li>CANCELLED：恢复失败或被取消。</li>
-</ul>
-</li>
-<li>AllowLoad：恢复期间是否允许导入。</li>
-<li>ReplicationNum：恢复指定的副本数。</li>
-<li>RestoreObjs：本次恢复涉及的表和分区的清单。</li>
-<li>CreateTime：作业创建时间。</li>
-<li>MetaPreparedTime：本地元数据生成完成时间。</li>
-<li>SnapshotFinishedTime：本地快照完成时间。</li>
-<li>DownloadFinishedTime：远端快照下载完成时间。</li>
-<li>FinishedTime：本次作业完成时间。</li>
-<li>UnfinishedTasks：在 <code class="docutils literal notranslate"><span class="pre">SNAPSHOTTING</span></code>，<code class="docutils literal notranslate"><span class="pre">DOWNLOADING</span></code>, <code class="docutils literal notranslate"><span class="pre">COMMITTING</span></code> 等阶段，会有多个子任务在同时进行，这里展示的当前阶段，未完成的子任务的 task id。</li>
-<li>TaskErrMsg：如果有子任务执行出错，这里会显示对应子任务的错误信息。</li>
-<li>Status：用于记录在整个作业过程中，可能出现的一些状态信息。</li>
-<li>Timeout：作业的超时时间，单位是秒。</li>
-</ul>
-</li>
-<li><p class="first">CANCEL BACKUP</p>
-<p>取消当前正在执行的备份作业。</p>
-</li>
-<li><p class="first">CANCEL RESTORE</p>
-<p>取消当前正在执行的恢复作业。</p>
-</li>
-<li><p class="first">DROP REPOSITORY</p>
-<p>删除已创建的远端仓库。删除仓库，仅仅是删除该仓库在 Doris 中的映射，不会删除实际的仓库数据。</p>
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-<li class="toctree-l3"><a class="reference internal" href="#id1">名词解释</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#id2">原理</a></li>
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-<li class="toctree-l4"><a class="reference internal" href="#group">查看 Group</a></li>
-<li class="toctree-l4"><a class="reference internal" href="#colocate-group">修改表 Colocate Group 属性</a></li>
-<li class="toctree-l4"><a class="reference internal" href="#id6">其他相关操作</a></li>
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-<h1>Colocation Join<a class="headerlink" href="#colocation-join" title="Permalink to this headline">¶</a></h1>
-<p>Colocation Join 是在 Doris 0.9 版本中引入的新功能。旨在为某些 Join 查询提供本地性优化，来减少数据在节点间的传输耗时，加速查询。</p>
-<p>最初的设计、实现和效果可以参阅 <a class="reference external" href="https://github.com/apache/incubator-doris/issues/245">ISSUE 245</a>。</p>
-<p>Colocation Join 功能经过一次改版，设计和使用方式和最初设计稍有不同。本文档主要介绍 Colocation Join 的原理、实现、使用方式和注意事项。</p>
-<div class="section" id="id1">
-<h2>名词解释<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>FE：Frontend，Doris 的前端节点。负责元数据管理和请求接入。</li>
-<li>BE：Backend，Doris 的后端节点。负责查询执行和数据存储。</li>
-<li>Colocation Group（CG）：一个 CG 中会包含一张及以上的 Table。在同一个 Group 内的 Table 有着相同的 Colocation Group Schema，并且有着相同的数据分片分布。</li>
-<li>Colocation Group Schema（CGS）：用于描述一个 CG 中的 Table，和 Colocation 相关的通用 Schema 信息。包括分桶列类型，分桶数以及副本数等。</li>
-</ul>
-</div>
-<div class="section" id="id2">
-<h2>原理<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<p>Colocation Join 功能，是将一组拥有相同 CGS 的 Table 组成一个 CG。并保证这些 Table 对应的数据分片会落在同一个 BE 节点上。使得当 CG 内的表进行分桶列上的 Join 操作时，可以通过直接进行本地数据 Join，减少数据在节点间的传输耗时。</p>
-<p>一个表的数据，最终会根据分桶列值 Hash、对桶数取模的后落在某一个分桶内。假设一个 Table 的分桶数为 8，则共有 <code class="docutils literal notranslate"><span class="pre">[0,</span> <span class="pre">1,</span> <span class="pre">2,</span> <span class="pre">3,</span> <span class="pre">4,</span> <span class="pre">5,</span> <span class="pre">6,</span> <span class="pre">7]</span></code> 8 个分桶（Bucket），我们称这样一个序列为一个 <code class="docutils literal notranslate"><span class="pre">BucketsSequence</span></code>。每个 Bucket 内会有一个或多个数据分片（Tablet）。当表为单 [...]
-<p>为了使得 Table 能够有相同的数据分布，同一 CG 内的 Table 必须保证以下属性相同：</p>
-<ol>
-<li><p class="first">分桶列和分桶数</p>
-<p>分桶列，即在建表语句中 <code class="docutils literal notranslate"><span class="pre">DISTRIBUTED</span> <span class="pre">BY</span> <span class="pre">HASH(col1,</span> <span class="pre">col2,</span> <span class="pre">...)</span></code> 中指定的列。分桶列决定了一张表的数据通过哪些列的值进行 Hash 划分到不同的 Tablet 中。同一 CG 内的 Table 必须保证分桶列的类型和数量完全一致，并且桶数一致，才能保证多张表的数据分片能够一一对应的进行分布控制。</p>
-</li>
-<li><p class="first">副本数</p>
-<p>同一个 CG 内所有表的所有分区（Partition）的副本数必须一致。如果不一致，可能出现某一个 Tablet 的某一个副本，在同一个 BE 上没有其他的表分片的副本对应。</p>
-</li>
-</ol>
-<p>同一个 CG 内的表，分区的个数、范围以及分区列的类型不要求一致。</p>
-<p>在固定了分桶列和分桶数后，同一个 CG 内的表会拥有相同的 BucketsSequnce。而副本数决定了每个分桶内的 Tablet 的多个副本，存放在哪些 BE 上。假设 BucketsSequnce 为 <code class="docutils literal notranslate"><span class="pre">[0,</span> <span class="pre">1,</span> <span class="pre">2,</span> <span class="pre">3,</span> <span class="pre">4,</span> <span class="pre">5,</span> <span class="pre">6,</span> <span class="pre">7]</span></code>，BE 节点有 <code class="docutils literal notranslate"><span class="pre">[A,</span> <span class="pre">B,</span> <spa [...]
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span>
-<span class="o">|</span> <span class="mi">0</span> <span class="o">|</span> <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="o">|</span> <span class="mi">2</span> <span class="o">|</span> <span class="o">|</span> <span class="mi">3</span> <span class="o">|</span> <span class="o">|</span> <span class="mi">4</span> <span class="o">|</span> <span class="o">|</span> <span class="mi">5</span> <span class="o">|</span> <span class="o">|</span> <span class [...]
-<span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span>
-<span class="o">|</span> <span class="n">A</span> <span class="o">|</span> <span class="o">|</span> <span class="n">B</span> <span class="o">|</span> <span class="o">|</span> <span class="n">C</span> <span class="o">|</span> <span class="o">|</span> <span class="n">D</span> <span class="o">|</span> <span class="o">|</span> <span class="n">A</span> <span class="o">|</span> <span class="o">|</span> <span class="n">B</span> <span class="o">|</span> <span class="o">|</span> <span class="n">C [...]
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">B</span> <span class="o">|</span> <span class="o">|</span> <span class="n">C</span> <span class="o">|</span> <span class="o">|</span> <span class="n">D</span> <span class="o">|</span> <span class="o">|</span> <span class="n">A</span> <span class="o">|</span> <span class="o">|</span> <span class="n">B</span> <span class="o">|</span> <span class="o">|</span> <span class="n">C</span> <span class="o">|</span> <span class="o">|</span> <span class="n">D [...]
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">C</span> <span class="o">|</span> <span class="o">|</span> <span class="n">D</span> <span class="o">|</span> <span class="o">|</span> <span class="n">A</span> <span class="o">|</span> <span class="o">|</span> <span class="n">B</span> <span class="o">|</span> <span class="o">|</span> <span class="n">C</span> <span class="o">|</span> <span class="o">|</span> <span class="n">D</span> <span class="o">|</span> <span class="o">|</span> <span class="n">A [...]
-<span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span>
-</pre></div>
-</div>
-<p>CG 内所有表的数据都会按照上面的规则进行统一分布，这样就保证了，分桶列值相同的数据都在同一个 BE 节点上，可以进行本地数据 Join。</p>
-</div>
-<div class="section" id="id3">
-<h2>使用方式<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id4">
-<h3>建表<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h3>
-<p>建表时，可以在 <code class="docutils literal notranslate"><span class="pre">PROPERTIES</span></code> 中指定属性 <code class="docutils literal notranslate"><span class="pre">"colocate_with"</span> <span class="pre">=</span> <span class="pre">"group_name"</span></code>，表示这个表是一个 Colocation Join 表，并且归属于一个指定的 Colocation Group。</p>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">CREATE</span> <span class="n">TABLE</span> <span class="n">tbl</span> <span class="p">(</span><span class="n">k1</span> <span class="nb">int</span><span class="p">,</span> <span class="n">v1</span> <span class="nb">int</span> <span class="nb">sum</span><span class="p">)</span>
-<span class="n">DISTRIBUTED</span> <span class="n">BY</span> <span class="n">HASH</span><span class="p">(</span><span class="n">k1</span><span class="p">)</span>
-<span class="n">BUCKETS</span> <span class="mi">8</span>
-<span class="n">PROPERTIES</span><span class="p">(</span>
- <span class="s2">"colocate_with"</span> <span class="o">=</span> <span class="s2">"group1"</span>
-<span class="p">);</span>
-</pre></div>
-</div>
-<p>如果指定的 Group 不存在，则 Doris 会自动创建一个只包含当前这张表的 Group。如果 Group 已存在，则 Doris 会检查当前表是否满足 Colocation Group Schema。如果满足，则会创建该表，并将该表加入 Group。同时，表会根据已存在的 Group 中的数据分布规则创建分片和副本。
-Group 归属于一个 Database，Group 的名字在一个 Database 内唯一。在内部存储是 Group 的全名为 <code class="docutils literal notranslate"><span class="pre">dbId_groupName</span></code>，但用户只感知 groupName。</p>
-</div>
-<div class="section" id="id5">
-<h3>删表<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<p>当 Group 中最后一张表彻底删除后（彻底删除是指从回收站中删除。通常，一张表通过 <code class="docutils literal notranslate"><span class="pre">DROP</span> <span class="pre">TABLE</span></code> 命令删除后，会在回收站默认停留一天的时间后，再删除），该 Group 也会被自动删除。</p>
-</div>
-<div class="section" id="group">
-<h3>查看 Group<a class="headerlink" href="#group" title="Permalink to this headline">¶</a></h3>
-<p>以下命令可以查看集群内已存在的 Group 信息。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">SHOW</span> <span class="n">PROC</span> <span class="s1">'/colocation_group'</span><span class="p">;</span>
-
-<span class="o">+-------------+--------------+--------------+------------+----------------+----------+----------+</span>
-<span class="o">|</span> <span class="n">GroupId</span> <span class="o">|</span> <span class="n">GroupName</span> <span class="o">|</span> <span class="n">TableIds</span> <span class="o">|</span> <span class="n">BucketsNum</span> <span class="o">|</span> <span class="n">ReplicationNum</span> <span class="o">|</span> <span class="n">DistCols</span> <span class="o">|</span> <span class="n">IsStable</span> <span class="o">|</span>
-<span class="o">+-------------+--------------+--------------+------------+----------------+----------+----------+</span>
-<span class="o">|</span> <span class="mf">10005.10008</span> <span class="o">|</span> <span class="mi">10005</span><span class="n">_group1</span> <span class="o">|</span> <span class="mi">10007</span><span class="p">,</span> <span class="mi">10040</span> <span class="o">|</span> <span class="mi">10</span> <span class="o">|</span> <span class="mi">3</span> <span class="o">|</span> <span class="nb">int</span><span class="p">(</span><span class="mi">11</span><span class [...]
-<span class="o">+-------------+--------------+--------------+------------+----------------+----------+----------+</span>
-</pre></div>
-</div>
-<ul class="simple">
-<li>GroupId： 一个 Group 的全集群唯一标识，前半部分为 db id，后半部分为 group id。</li>
-<li>GroupName： Group 的全名。</li>
-<li>TabletIds： 该 Group 包含的 Table 的 id 列表。</li>
-<li>BucketsNum： 分桶数。</li>
-<li>ReplicationNum： 副本数。</li>
-<li>DistCols： Distribution columns，即分桶列类型。</li>
-<li>IsStable： 该 Group 是否稳定（稳定的定义，见 <code class="docutils literal notranslate"><span class="pre">Colocation</span> <span class="pre">副本均衡和修复</span></code> 一节）。</li>
-</ul>
-<p>通过以下命令可以进一步查看一个 Group 的数据分布情况：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">SHOW</span> <span class="n">PROC</span> <span class="s1">'/colocation_group/10005.10008'</span><span class="p">;</span>
-
-<span class="o">+-------------+---------------------+</span>
-<span class="o">|</span> <span class="n">BucketIndex</span> <span class="o">|</span> <span class="n">BackendIds</span> <span class="o">|</span>
-<span class="o">+-------------+---------------------+</span>
-<span class="o">|</span> <span class="mi">0</span> <span class="o">|</span> <span class="mi">10004</span><span class="p">,</span> <span class="mi">10002</span><span class="p">,</span> <span class="mi">10001</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> <span class="mi">10003</span><span class="p">,</span> <span class="mi">10002</span><span class="p">,</span> <span class="mi">10004</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">2</span> <span class="o">|</span> <span class="mi">10002</span><span class="p">,</span> <span class="mi">10004</span><span class="p">,</span> <span class="mi">10001</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">3</span> <span class="o">|</span> <span class="mi">10003</span><span class="p">,</span> <span class="mi">10002</span><span class="p">,</span> <span class="mi">10004</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">4</span> <span class="o">|</span> <span class="mi">10002</span><span class="p">,</span> <span class="mi">10004</span><span class="p">,</span> <span class="mi">10003</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">5</span> <span class="o">|</span> <span class="mi">10003</span><span class="p">,</span> <span class="mi">10002</span><span class="p">,</span> <span class="mi">10001</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">6</span> <span class="o">|</span> <span class="mi">10003</span><span class="p">,</span> <span class="mi">10004</span><span class="p">,</span> <span class="mi">10001</span> <span class="o">|</span>
-<span class="o">|</span> <span class="mi">7</span> <span class="o">|</span> <span class="mi">10003</span><span class="p">,</span> <span class="mi">10004</span><span class="p">,</span> <span class="mi">10002</span> <span class="o">|</span>
-<span class="o">+-------------+---------------------+</span>
-</pre></div>
-</div>
-<ul class="simple">
-<li>BucketIndex： 分桶序列的下标。</li>
-<li>BackendIds： 分桶中数据分片所在的 BE 节点 id 列表。</li>
-</ul>
-<blockquote>
-<div>以上命令需要 AMDIN 权限。暂不支持普通用户查看。</div></blockquote>
-</div>
-<div class="section" id="colocate-group">
-<h3>修改表 Colocate Group 属性<a class="headerlink" href="#colocate-group" title="Permalink to this headline">¶</a></h3>
-<p>可以对一个已经创建的表，修改其 Colocation Group 属性。示例：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">tbl</span> <span class="pre">SET</span> <span class="pre">("colocate_with"</span> <span class="pre">=</span> <span class="pre">"group2");</span></code></p>
-<ul class="simple">
-<li>如果该表之前没有指定过 Group，则该命令检查 Schema，并将该表加入到该 Group（Group 不存在则会创建）。</li>
-<li>如果该表之前有指定其他 Group，则该命令会先将该表从原有 Group 中移除，并加入新 Group（Group 不存在则会创建）。</li>
-</ul>
-<p>也可以通过以下命令，删除一个表的 Colocation 属性：</p>
-<p><code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">TABLE</span> <span class="pre">tbl</span> <span class="pre">SET</span> <span class="pre">("colocate_with"</span> <span class="pre">=</span> <span class="pre">"");</span></code></p>
-</div>
-<div class="section" id="id6">
-<h3>其他相关操作<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h3>
-<p>当对一个具有 Colocation 属性的表进行增加分区（ADD PARTITION）、修改副本数时，Doris 会检查修改是否会违反 Colocation Group Schema，如果违反则会拒绝。</p>
-</div>
-</div>
-<div class="section" id="colocation">
-<h2>Colocation 副本均衡和修复<a class="headerlink" href="#colocation" title="Permalink to this headline">¶</a></h2>
-<p>Colocation 表的副本分布需要遵循 Group 中指定的分布，所以在副本修复和均衡方面和普通分片有所区别。</p>
-<p>Group 自身有一个 Stable 属性，当 Stable 为 true 时，表示当前 Group 内的表的所有分片没有正在进行变动，Colocation 特性可以正常使用。当 Stable 为 false 时（Unstable），表示当前 Group 内有部分表的分片正在做修复或迁移，此时，相关表的 Colocation Join 将退化为普通 Join。</p>
-<div class="section" id="id7">
-<h3>副本修复<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h3>
-<p>副本只能存储在指定的 BE 节点上。所以当某个 BE 不可用时（宕机、Decommission 等），需要寻找一个新的 BE 进行替换。Doris 会优先寻找负载最低的 BE 进行替换。替换后，该 Bucket 内的所有在旧 BE 上的数据分片都要做修复。迁移过程中，Group 被标记为 Unstable。</p>
-</div>
-<div class="section" id="id8">
-<h3>副本均衡<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
-<p>Doris 会尽力将 Colocation 表的分片均匀分布在所有 BE 节点上。对于普通表的副本均衡，是以单副本为粒度的，即单独为每一个副本寻找负载较低的 BE 节点即可。而 Colocation 表的均衡是 Bucket 级别的，即一个 Bucket 内的所有副本都会一起迁移。我们采用一个简单的均衡算法，即在不考虑副本实际大小，而只根据副本数量，将 BucketsSequnce 均匀的分布在所有 BE 上。具体算法可以参阅 <code class="docutils literal notranslate"><span class="pre">ColocateTableBalancer.java</span></code> 中的代码注释。</p>
-<blockquote>
-<div><p>注1：当前的 Colocation 副本均衡和修复算法，对于异构部署的 Doris 集群效果可能不佳。所谓异构部署，即 BE 节点的磁盘容量、数量、磁盘类型（SSD 和 HDD）不一致。在异构部署情况下，可能出现小容量的 BE 节点和大容量的 BE 节点存储了相同的副本数量。</p>
-<p>注2：当一个 Group 处于 Unstable 状态时，其中的表的 Join 将退化为普通 Join。此时可能会极大降低集群的查询性能。如果不希望系统自动均衡，可以设置 FE 的配置项 <code class="docutils literal notranslate"><span class="pre">disable_colocate_balance</span></code> 来禁止自动均衡。然后在合适的时间打开即可。（具体参阅 <code class="docutils literal notranslate"><span class="pre">高级操作</span></code> 一节）</p>
-</div></blockquote>
-</div>
-</div>
-<div class="section" id="id9">
-<h2>查询<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h2>
-<p>对 Colocation 表的查询方式和普通表一样，用户无需感知 Colocation 属性。如果 Colocation 表所在的 Group 处于 Unstable 状态，将自动退化为普通 Join。</p>
-<p>举例说明：</p>
-<p>表1：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>CREATE TABLE `tbl1` (
- `k1` date NOT NULL COMMENT "",
- `k2` int(11) NOT NULL COMMENT "",
- `v1` int(11) SUM NOT NULL COMMENT ""
-) ENGINE=OLAP
-AGGREGATE KEY(`k1`, `k2`)
-PARTITION BY RANGE(`k1`)
-(
- PARTITION p1 VALUES LESS THAN ('2019-05-31'),
- PARTITION p2 VALUES LESS THAN ('2019-06-30')
-)
-DISTRIBUTED BY HASH(`k2`) BUCKETS 8
-PROPERTIES (
- "colocate_with" = "group1"
-);
-</pre></div>
-</div>
-<p>表2：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>CREATE TABLE `tbl2` (
- `k1` datetime NOT NULL COMMENT "",
- `k2` int(11) NOT NULL COMMENT "",
- `v1` double SUM NOT NULL COMMENT ""
-) ENGINE=OLAP
-AGGREGATE KEY(`k1`, `k2`)
-DISTRIBUTED BY HASH(`k2`) BUCKETS 8
-PROPERTIES (
- "colocate_with" = "group1"
-);
-</pre></div>
-</div>
-<p>查看查询计划：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>DESC SELECT * FROM tbl1 INNER JOIN tbl2 ON (tbl1.k2 = tbl2.k2);
-
-+----------------------------------------------------+
-| Explain String |
-+----------------------------------------------------+
-| PLAN FRAGMENT 0 |
-| OUTPUT EXPRS:`tbl1`.`k1` | |
-| PARTITION: RANDOM |
-| |
-| RESULT SINK |
-| |
-| 2:HASH JOIN |
-| | join op: INNER JOIN |
-| | hash predicates: |
-| | colocate: true |
-| | `tbl1`.`k2` = `tbl2`.`k2` |
-| | tuple ids: 0 1 |
-| | |
-| |----1:OlapScanNode |
-| | TABLE: tbl2 |
-| | PREAGGREGATION: OFF. Reason: null |
-| | partitions=0/1 |
-| | rollup: null |
-| | buckets=0/0 |
-| | cardinality=-1 |
-| | avgRowSize=0.0 |
-| | numNodes=0 |
-| | tuple ids: 1 |
-| | |
-| 0:OlapScanNode |
-| TABLE: tbl1 |
-| PREAGGREGATION: OFF. Reason: No AggregateInfo |
-| partitions=0/2 |
-| rollup: null |
-| buckets=0/0 |
-| cardinality=-1 |
-| avgRowSize=0.0 |
-| numNodes=0 |
-| tuple ids: 0 |
-+----------------------------------------------------+
-</pre></div>
-</div>
-<p>如果 Colocation Join 生效，则 Hash Join 节点会显示 <code class="docutils literal notranslate"><span class="pre">colocate:</span> <span class="pre">true</span></code>。</p>
-<p>如果没有生效，则查询计划如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>+----------------------------------------------------+
-| Explain String |
-+----------------------------------------------------+
-| PLAN FRAGMENT 0 |
-| OUTPUT EXPRS:`tbl1`.`k1` | |
-| PARTITION: RANDOM |
-| |
-| RESULT SINK |
-| |
-| 2:HASH JOIN |
-| | join op: INNER JOIN (BROADCAST) |
-| | hash predicates: |
-| | colocate: false, reason: group is not stable |
-| | `tbl1`.`k2` = `tbl2`.`k2` |
-| | tuple ids: 0 1 |
-| | |
-| |----3:EXCHANGE |
-| | tuple ids: 1 |
-| | |
-| 0:OlapScanNode |
-| TABLE: tbl1 |
-| PREAGGREGATION: OFF. Reason: No AggregateInfo |
-| partitions=0/2 |
-| rollup: null |
-| buckets=0/0 |
-| cardinality=-1 |
-| avgRowSize=0.0 |
-| numNodes=0 |
-| tuple ids: 0 |
-| |
-| PLAN FRAGMENT 1 |
-| OUTPUT EXPRS: |
-| PARTITION: RANDOM |
-| |
-| STREAM DATA SINK |
-| EXCHANGE ID: 03 |
-| UNPARTITIONED |
-| |
-| 1:OlapScanNode |
-| TABLE: tbl2 |
-| PREAGGREGATION: OFF. Reason: null |
-| partitions=0/1 |
-| rollup: null |
-| buckets=0/0 |
-| cardinality=-1 |
-| avgRowSize=0.0 |
-| numNodes=0 |
-| tuple ids: 1 |
-+----------------------------------------------------+
-</pre></div>
-</div>
-<p>HASH JOIN 节点会显示对应原因：<code class="docutils literal notranslate"><span class="pre">colocate:</span> <span class="pre">false,</span> <span class="pre">reason:</span> <span class="pre">group</span> <span class="pre">is</span> <span class="pre">not</span> <span class="pre">stable</span></code>。同时会有一个 EXCHANGE 节点生成。</p>
-</div>
-<div class="section" id="id10">
-<h2>高级操作<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE 配置项<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<ul>
-<li><p class="first">disable_colocate_relocate</p>
-<p>是否关闭 Doris 的自动 Colocation 副本修复。默认为 false，即不关闭。该参数只影响 Colocation 表的副本修复，不影响普通表。</p>
-</li>
-<li><p class="first">disable_colocate_balance</p>
-<p>是否关闭 Doris 的自动 Colocation 副本均衡。默认为 false，即不关闭。该参数只影响 Colocation 表的副本均衡，不影响普通表。</p>
-</li>
-</ul>
-<p>以上参数可以动态修改，设置方式请参阅 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">ADMIN</span> <span class="pre">SHOW</span> <span class="pre">CONFIG;</span></code> 和 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">ADMIN</span> <span class="pre">SET</span> <span class="pre">CONFIG;</span></code>。</p>
-<ul>
-<li><p class="first">disable_colocate_join</p>
-<p>是否关闭 Colocation Join 功能。在 0.10 及之前的版本，默认为 true，即关闭。在之后的某个版本中将默认为 false，即开启。</p>
-</li>
-<li><p class="first">use_new_tablet_scheduler</p>
-<p>在 0.10 及之前的版本中，新的副本调度逻辑与 Colocation Join 功能不兼容，所以在 0.10 及之前版本，如果 <code class="docutils literal notranslate"><span class="pre">disable_colocate_join</span> <span class="pre">=</span> <span class="pre">false</span></code>，则需设置 <code class="docutils literal notranslate"><span class="pre">use_new_tablet_scheduler</span> <span class="pre">=</span> <span class="pre">false</span></code>，即关闭新的副本调度器。之后的版本中，<code class="docutils literal notranslate"><span class="pre">use_new_tablet_scheduler</s [...]
-</li>
-</ul>
-</div>
-<div class="section" id="http-restful-api">
-<h3>HTTP Restful API<a class="headerlink" href="#http-restful-api" title="Permalink to this headline">¶</a></h3>
-<p>Doris 提供了几个和 Colocation Join 有关的 HTTP Restful API，用于查看和修改 Colocation Group。</p>
-<p>该 API 实现在 FE 端，使用 <code class="docutils literal notranslate"><span class="pre">fe_host:fe_http_port</span></code> 进行访问。需要 ADMIN 权限。</p>
-<ol>
-<li><p class="first">查看集群的全部 Colocation 信息</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>GET /api/colocate
-
-返回以 Json 格式表示内部 Colocation 信息。
-
-{
- "colocate_meta": {
- "groupName2Id": {
- "g1": {
- "dbId": 10005,
- "grpId": 10008
- }
- },
- "group2Tables": {},
- "table2Group": {
- "10007": {
- "dbId": 10005,
- "grpId": 10008
- },
- "10040": {
- "dbId": 10005,
- "grpId": 10008
- }
- },
- "group2Schema": {
- "10005.10008": {
- "groupId": {
- "dbId": 10005,
- "grpId": 10008
- },
- "distributionColTypes": [{
- "type": "INT",
- "len": -1,
- "isAssignedStrLenInColDefinition": false,
- "precision": 0,
- "scale": 0
- }],
- "bucketsNum": 10,
- "replicationNum": 2
- }
- },
- "group2BackendsPerBucketSeq": {
- "10005.10008": [
- [10004, 10002],
- [10003, 10002],
- [10002, 10004],
- [10003, 10002],
- [10002, 10004],
- [10003, 10002],
- [10003, 10004],
- [10003, 10004],
- [10003, 10004],
- [10002, 10004]
- ]
- },
- "unstableGroups": []
- },
- "status": "OK"
-}
-</pre></div>
-</div>
-</li>
-<li><p class="first">将 Group 标记为 Stable 或 Unstable</p>
-<ul>
-<li><p class="first">标记为 Stable</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>POST /api/colocate/group_stable?db_id=10005&group_id=10008
-
-返回：200
-</pre></div>
-</div>
-</li>
-<li><p class="first">标记为 Unstable</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>DELETE /api/colocate/group_stable?db_id=10005&group_id=10008
-
-返回：200
-</pre></div>
-</div>
-</li>
-</ul>
-</li>
-<li><p class="first">设置 Group 的数据分布</p>
-<p>该接口可以强制设置某一 Group 的数分布。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>POST /api/colocate/bucketseq?db_id=10005&group_id= 10008
-
-Body:
-[[10004,10002],[10003,10002],[10002,10004],[10003,10002],[10002,10004],[10003,10002],[10003,10004],[10003,10004],[10003,10004],[10002,10004]]
-
-返回 200
-</pre></div>
-</div>
-<p>其中 Body 是以嵌套数组表示的 BucketsSequence 以及每个 Bucket 中分片分布所在 BE 的 id。</p>
-<p>注意，使用该命令，可能需要将 FE 的配置 <code class="docutils literal notranslate"><span class="pre">disable_colocate_relocate</span></code> 和 <code class="docutils literal notranslate"><span class="pre">disable_colocate_balance</span></code> 设为 true。即关闭系统自动的 Colocation 副本修复和均衡。否则可能在修改后，会被系统自动重置。</p>
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-<li class="toctree-l3"><a class="reference internal" href="#id2">名词解释</a></li>
-<li class="toctree-l3"><a class="reference internal" href="#id3">原理</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="#id4">查询计划拆分</a></li>
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-</ul>
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-
- <div class="section" id="id1">
-<h1>数据导出<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h1>
-<p>数据导出（Export）是 Doris 提供的一种将数据导出的功能。该功能可以将用户指定的表或分区的数据，以文本的格式，通过 Broker 进程导出到远端存储上，如 HDFS/BOS 等。</p>
-<p>本文档主要介绍 Export 的基本原理、使用方式、最佳实践以及注意事项。</p>
-<div class="section" id="id2">
-<h2>名词解释<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>FE：Frontend，Doris 的前端节点。负责元数据管理和请求接入。</li>
-<li>BE：Backend，Doris 的后端节点。负责查询执行和数据存储。</li>
-<li>Broker：Doris 可以通过 Broker 进程对远端存储进行文件操作。</li>
-<li>Tablet：数据分片。一个表会划分成多个数据分片。</li>
-</ul>
-</div>
-<div class="section" id="id3">
-<h2>原理<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>用户提交一个 Export 作业后。Doris 会统计这个作业涉及的所有 Tablet。然后对这些 Tablet 进行分组，每组生成一个特殊的查询计划。该查询计划会读取所包含的 Tablet 上的数据，然后通过 Broker 将数据写到远端存储指定的路径中。</p>
-<p>总体的调度方式如下:</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+--------+</span>
-<span class="o">|</span> <span class="n">Client</span> <span class="o">|</span>
-<span class="o">+---+----+</span>
- <span class="o">|</span> <span class="mf">1.</span> <span class="n">Submit</span> <span class="n">Job</span>
- <span class="o">|</span>
-<span class="o">+---</span><span class="n">v</span><span class="o">--------------------+</span>
-<span class="o">|</span> <span class="n">FE</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-------------------+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">ExportPendingTask</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-------------------+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="mf">2.</span> <span class="n">Generate</span> <span class="n">Tasks</span>
-<span class="o">|</span> <span class="o">+--------------------+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">ExportExporingTask</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+--------------------+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-----------+</span> <span class="o">|</span> <span class="o">+----+</span> <span class="o">+------+</span> <span class="o">+---------+</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">QueryPlan</span> <span class="o">+----------------></span> <span class="n">BE</span> <span class="o">+---></span><span class="n">Broker</span><span class="o">+---></span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-----------+</span> <span class="o">|</span> <span class="o">+----+</span> <span class="o">+------+</span> <span class="o">|</span> <span class="n">Remote</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-----------+</span> <span class="o">|</span> <span class="o">+----+</span> <span class="o">+------+</span> <span class="o">|</span> <span class="n">Storage</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">QueryPlan</span> <span class="o">+----------------></span> <span class="n">BE</span> <span class="o">+---></span><span class="n">Broker</span><span class="o">+---></span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-----------+</span> <span class="o">|</span> <span class="o">+----+</span> <span class="o">+------+</span> <span class="o">+---------+</span>
-<span class="o">+------------------------+</span> <span class="mf">3.</span> <span class="n">Execute</span> <span class="n">Tasks</span>
-</pre></div>
-</div>
-<ol class="simple">
-<li>用户提交一个 Export 作业到 FE。</li>
-<li>FE 的 Export 调度器会通过两阶段来执行一个 Export 作业：<ol>
-<li>PENDING：FE 生成 ExportPendingTask，向 BE 发送 snapshot 命令，对所有涉及到的 Tablet 做一个快照。并生成多个查询计划。</li>
-<li>EXPORTING：FE 生成 ExportExporingTask，开始执行查询计划。</li>
-</ol>
-</li>
-</ol>
-<div class="section" id="id4">
-<h3>查询计划拆分<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h3>
-<p>Export 作业会生成多个查询计划，每个查询计划负责扫描一部分 Tablet。每个查询计划扫描的 Tablet 个数由 FE 配置参数 <code class="docutils literal notranslate"><span class="pre">export_tablet_num_per_task</span></code> 指定，默认为 5。即假设一共 100 个 Tablet，则会生成 20 个查询计划。用户也可以在提交作业时，通过作业属性 <code class="docutils literal notranslate"><span class="pre">tablet_num_per_task</span></code> 指定这个数值。</p>
-<p>一个作业的多个查询计划顺序执行。</p>
-</div>
-<div class="section" id="id5">
-<h3>查询计划执行<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<p>一个查询计划扫描多个分片，将读取的数据以行的形式组织，每 1024 行为一个 batch，调用 Broker 写入到远端存储上。</p>
-<p>查询计划遇到错误会整体自动重试 3 次。如果一个查询计划重试 3 次依然失败，则整个作业失败。</p>
-<p>Doris 会首先在指定的远端存储的路径中，建立一个名为 <code class="docutils literal notranslate"><span class="pre">__doris_export_tmp_12345</span></code> 的临时目录（其中 <code class="docutils literal notranslate"><span class="pre">12345</span></code> 为作业 id）。导出的数据首先会写入这个临时目录。每个查询计划会生成一个文件，文件名示例：</p>
-<p><code class="docutils literal notranslate"><span class="pre">export-data-c69fcf2b6db5420f-a96b94c1ff8bccef-1561453713822</span></code></p>
-<p>其中 <code class="docutils literal notranslate"><span class="pre">c69fcf2b6db5420f-a96b94c1ff8bccef</span></code> 为查询计划的 query id。<code class="docutils literal notranslate"><span class="pre">1561453713822</span></code> 为文件生成的时间戳。</p>
-<p>当所有数据都导出后，Doris 会将这些文件 rename 到用户指定的路径中。</p>
-</div>
-</div>
-<div class="section" id="id6">
-<h2>使用示例<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<p>Export 的详细命令可以通过 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">EXPORT;</span></code> 。举例如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">EXPORT</span> <span class="n">TABLE</span> <span class="n">db1</span><span class="o">.</span><span class="n">tbl1</span>
-<span class="n">PARTITION</span> <span class="p">(</span><span class="n">p1</span><span class="p">,</span><span class="n">p2</span><span class="p">)</span>
-<span class="n">TO</span> <span class="s2">"hdfs://host/path/to/export/"</span>
-<span class="n">PROPERTIES</span>
-<span class="p">(</span>
- <span class="s2">"column_separator"</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span>
- <span class="s2">"exec_mem_limit"</span><span class="o">=</span><span class="s2">"2147483648"</span><span class="p">,</span>
- <span class="s2">"timeout"</span> <span class="o">=</span> <span class="s2">"3600"</span>
-<span class="p">)</span>
-<span class="n">WITH</span> <span class="n">BROKER</span> <span class="s2">"hdfs"</span>
-<span class="p">(</span>
- <span class="s2">"username"</span> <span class="o">=</span> <span class="s2">"user"</span><span class="p">,</span>
- <span class="s2">"password"</span> <span class="o">=</span> <span class="s2">"passwd"</span><span class="p">,</span>
-<span class="p">);</span>
-</pre></div>
-</div>
-<ul class="simple">
-<li><code class="docutils literal notranslate"><span class="pre">column_separator</span></code>：列分隔符。默认为 <code class="docutils literal notranslate"><span class="pre">\t</span></code>。</li>
-<li><code class="docutils literal notranslate"><span class="pre">line_delimiter</span></code>：行分隔符。默认为 <code class="docutils literal notranslate"><span class="pre">\n</span></code>。</li>
-<li><code class="docutils literal notranslate"><span class="pre">exec_mem_limit</span></code>： 表示 Export 作业中，一个查询计划在单个 BE 上的内存使用限制。默认 2GB。单位字节。</li>
-<li><code class="docutils literal notranslate"><span class="pre">timeout</span></code>：作业超时时间。默认 2小时。单位秒。</li>
-<li><code class="docutils literal notranslate"><span class="pre">tablet_num_per_task</span></code>：每个查询计划分配的最大分片数。默认为 5。</li>
-</ul>
-<p>提交作业后，可以通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">EXPORT</span></code> 命令查询导入作业状态。结果举例如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">JobId</span><span class="p">:</span> <span class="mi">14008</span>
- <span class="n">State</span><span class="p">:</span> <span class="n">FINISHED</span>
- <span class="n">Progress</span><span class="p">:</span> <span class="mi">100</span><span class="o">%</span>
- <span class="n">TaskInfo</span><span class="p">:</span> <span class="p">{</span><span class="s2">"partitions"</span><span class="p">:[</span><span class="s2">"*"</span><span class="p">],</span><span class="s2">"exec mem limit"</span><span class="p">:</span><span class="mi">2147483648</span><span class="p">,</span><span class="s2">"column separator"</span><span class="p">:</span><span class="s2">","</span><span class="p">,</span><span cl [...]
- <span class="n">Path</span><span class="p">:</span> <span class="n">bos</span><span class="p">:</span><span class="o">//</span><span class="n">bj</span><span class="o">-</span><span class="n">test</span><span class="o">-</span><span class="n">cmy</span><span class="o">/</span><span class="n">export</span><span class="o">/</span>
-<span class="n">CreateTime</span><span class="p">:</span> <span class="mi">2019</span><span class="o">-</span><span class="mi">06</span><span class="o">-</span><span class="mi">25</span> <span class="mi">17</span><span class="p">:</span><span class="mi">08</span><span class="p">:</span><span class="mi">24</span>
- <span class="n">StartTime</span><span class="p">:</span> <span class="mi">2019</span><span class="o">-</span><span class="mi">06</span><span class="o">-</span><span class="mi">25</span> <span class="mi">17</span><span class="p">:</span><span class="mi">08</span><span class="p">:</span><span class="mi">28</span>
-<span class="n">FinishTime</span><span class="p">:</span> <span class="mi">2019</span><span class="o">-</span><span class="mi">06</span><span class="o">-</span><span class="mi">25</span> <span class="mi">17</span><span class="p">:</span><span class="mi">08</span><span class="p">:</span><span class="mi">34</span>
- <span class="n">Timeout</span><span class="p">:</span> <span class="mi">3600</span>
- <span class="n">ErrorMsg</span><span class="p">:</span> <span class="n">N</span><span class="o">/</span><span class="n">A</span>
-</pre></div>
-</div>
-<ul class="simple">
-<li>JobId：作业的唯一 ID</li>
-<li>State：作业状态：<ul>
-<li>PENDING：作业待调度</li>
-<li>EXPORING：数据导出中</li>
-<li>FINISHED：作业成功</li>
-<li>CANCELLED：作业失败</li>
-</ul>
-</li>
-<li>Progress：作业进度。该进度以查询计划为单位。假设一共 10 个查询计划，当前已完成 3 个，则进度为 30%。</li>
-<li>TaskInfo：以 Json 格式展示的作业信息：<ul>
-<li>db：数据库名</li>
-<li>tbl：表名</li>
-<li>partitions：指定导出的分区。<code class="docutils literal notranslate"><span class="pre">*</span></code> 表示所有分区。</li>
-<li>exec mem limit：查询计划内存使用限制。单位字节。</li>
-<li>column separator：导出文件的列分隔符。</li>
-<li>line delimiter：导出文件的行分隔符。</li>
-<li>tablet num：涉及的总 Tablet 数量。</li>
-<li>broker：使用的 broker 的名称。</li>
-<li>coord num：查询计划的个数。</li>
-</ul>
-</li>
-<li>Path：远端存储上的导出路径。</li>
-<li>CreateTime/StartTime/FinishTime：作业的创建时间、开始调度时间和结束时间。</li>
-<li>Timeout：作业超时时间。单位是秒。该时间从 CreateTime 开始计算。</li>
-<li>ErrorMsg：如果作业出现错误，这里会显示错误原因。</li>
-</ul>
-</div>
-<div class="section" id="id7">
-<h2>最佳实践<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id8">
-<h3>查询计划的拆分<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
-<p>一个 Export 作业有多少查询计划需要执行，取决于总共有多少 Tablet，以及一个查询计划最多可以分配多少个 Tablet。因为多个查询计划是串行执行的，所以如果让一个查询计划处理更多的分片，则可以减少作业的执行时间。但如果查询计划出错（比如调用 Broker 的 RPC 失败，远端存储出现抖动等），过多的 Tablet 会导致一个查询计划的重试成本变高。所以需要合理安排查询计划的个数以及每个查询计划所需要扫描的分片数，在执行时间和执行成功率之间做出平衡。一般建议一个查询计划扫描的数据量在 3-5 GB内（一个表的 Tablet 的大小以及个数可以通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">TABLET</span> <span class="pre">FROM</span> <span class="pre">tbl_name;</span></code> 语句查看。）。</p>
-</div>
-<div class="section" id="exec-mem-limit">
-<h3>exec_mem_limit<a class="headerlink" href="#exec-mem-limit" title="Permalink to this headline">¶</a></h3>
-<p>通常一个 Export 作业的查询计划只有 <code class="docutils literal notranslate"><span class="pre">扫描</span></code>-<code class="docutils literal notranslate"><span class="pre">导出</span></code> 两部分，不涉及需要太多内存的计算逻辑。所以通常 2GB 的默认内存限制可以满足需求。但在某些场景下，比如一个查询计划，在同一个 BE 上需要扫描的 Tablet 过多，或者 Tablet 的数据版本过多时，可能会导致内存不足。此时需要通过这个参数设置更大的内存，比如 4GB、8GB 等。</p>
-</div>
-</div>
-<div class="section" id="id9">
-<h2>注意事项<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>不建议一次性导出大量数据。一个 Export 作业建议的导出数据量最大在几十 GB。过大的导出会导致更多的垃圾文件和更高的重试成本。</li>
-<li>如果表数据量过大，建议按照分区导出。</li>
-<li>在 Export 作业运行过程中，如果 FE 发生重启或切主，则 Export 作业会失败，需要用户重新提交。</li>
-<li>如果 Export 作业运行失败，在远端存储中产生的 <code class="docutils literal notranslate"><span class="pre">__doris_export_tmp_xxx</span></code> 临时目录，以及已经生成的文件不会被删除，需要用户手动删除。</li>
-<li>如果 Export 作业运行成功，在远端存储中产生的 <code class="docutils literal notranslate"><span class="pre">__doris_export_tmp_xxx</span></code> 目录，根据远端存储的文件系统语义，可能会保留，也可能会被清除。比如在百度对象存储（BOS）中，通过 rename 操作将一个目录中的最后一个文件移走后，该目录也会被删除。如果该目录没有被清除，用户可以手动清除。</li>
-<li>当 Export 运行完成后（成功或失败），FE 发生重启或切主，则 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">EXPORT</span></code> 展示的作业的部分信息会丢失，无法查看。</li>
-<li>Export 作业只会导出 Base 表的数据，不会导出 Rollup Index 的数据。</li>
-<li>Export 作业会扫描数据，占用 IO 资源，可能会影响系统的查询延迟。</li>
-</ul>
-</div>
-<div class="section" id="id10">
-<h2>相关配置<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<ul class="simple">
-<li><code class="docutils literal notranslate"><span class="pre">export_checker_interval_second</span></code>：Export 作业调度器的调度间隔，默认为 5 秒。设置该参数需重启 FE。</li>
-<li><code class="docutils literal notranslate"><span class="pre">export_running_job_num_limit</span></code>：正在运行的 Export 作业数量限制。如果超过，则作业将等待并处于 PENDING 状态。默认为 5，可以运行时调整。</li>
-<li><code class="docutils literal notranslate"><span class="pre">export_task_default_timeout_second</span></code>：Export 作业默认超时时间。默认为 2 小时。可以运行时调整。</li>
-<li><code class="docutils literal notranslate"><span class="pre">export_tablet_num_per_task</span></code>：一个查询计划负责的最大分片数。默认为 5。</li>
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diff --git a/content/Docs/cn/administrator-guide/http-actions/cancel-label.html b/content/Docs/cn/administrator-guide/http-actions/cancel-label.html
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-<!DOCTYPE html>
-<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]-->
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-<h1>CANCEL LABEL<a class="headerlink" href="#cancel-label" title="Permalink to this headline">¶</a></h1>
-<div class="section" id="description">
-<h2>description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>NAME:
- cancel_label: cancel a transaction with label
-
-SYNOPSIS
- curl -u user:passwd -XPOST http://host:port/api/{db}/{label}/_cancel
-
-DESCRIPTION
- 该命令用于cancel一个指定Label对应的事务，事务在Prepare阶段能够被成功cancel
-
-RETURN VALUES
- 执行完成后，会以Json格式返回这次导入的相关内容。当前包括一下字段
- Status: 是否成功cancel
- Success: 成功cancel事务
- 其他: cancel失败
- Message: 具体的失败信息
-
-ERRORS
-</pre></div>
-</div>
-</div>
-<div class="section" id="example">
-<h2>example<a class="headerlink" href="#example" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="mf">1.</span> <span class="n">cancel</span> <span class="n">testDb</span><span class="p">,</span> <span class="n">testLabel的作业</span>
- <span class="n">curl</span> <span class="o">-</span><span class="n">u</span> <span class="n">root</span> <span class="o">-</span><span class="n">XPOST</span> <span class="n">http</span><span class="p">:</span><span class="o">//</span><span class="n">host</span><span class="p">:</span><span class="n">port</span><span class="o">/</span><span class="n">api</span><span class="o">/</span><span class="n">testDb</span><span class="o">/</span><span class="n">testLabel</span><span class="o">/ [...]
-</pre></div>
-</div>
-</div>
-<div class="section" id="keyword">
-<h2>keyword<a class="headerlink" href="#keyword" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>CANCEL，LABEL
-</pre></div>
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-<p>用户可以通过该 HTTP 接口获取 FE 的日志文件。</p>
-<div class="section" id="id1">
-<h2>日志类型<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<p>支持获取以下类型的 FE 日志：</p>
-<ol>
-<li><p class="first">fe.audit.log（审计日志）</p>
-<p>审计日志记录了对应 FE 节点的所有请求语句已经请求的信息。审计日志的文件命名规则如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">fe</span><span class="o">.</span><span class="n">audit</span><span class="o">.</span><span class="n">log</span> <span class="c1"># 当前的最新日志</span>
-<span class="n">fe</span><span class="o">.</span><span class="n">audit</span><span class="o">.</span><span class="n">log</span><span class="o">.</span><span class="mf">20190603.1</span> <span class="c1"># 对应日期的审计日志，当对应日期的日志大小超过 1GB 后，会生成序号后缀。序号越小的日志，内容越新。</span>
-<span class="n">fe</span><span class="o">.</span><span class="n">audit</span><span class="o">.</span><span class="n">log</span><span class="o">.</span><span class="mf">20190603.2</span>
-<span class="n">fe</span><span class="o">.</span><span class="n">audit</span><span class="o">.</span><span class="n">log</span><span class="o">.</span><span class="mf">20190602.1</span>
-<span class="o">...</span>
-</pre></div>
-</div>
-</li>
-</ol>
-</div>
-<div class="section" id="id2">
-<h2>接口示例<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<ol>
-<li><p class="first">获取对应类型的日志文件列表</p>
-<p>示例：</p>
-<p><code class="docutils literal notranslate"><span class="pre">curl</span> <span class="pre">-X</span> <span class="pre">HEAD</span> <span class="pre">-uuser:passwd</span> <span class="pre">http://fe_host:http_port/api/get_log_file?type=fe.audit.log</span></code></p>
-<p>返回结果：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">HTTP</span><span class="o">/</span><span class="mf">1.1</span> <span class="mi">200</span> <span class="n">OK</span>
-<span class="n">file_infos</span><span class="p">:</span> <span class="p">{</span><span class="s2">"fe.audit.log"</span><span class="p">:</span><span class="mi">24759</span><span class="p">,</span><span class="s2">"fe.audit.log.20190528.1"</span><span class="p">:</span><span class="mi">132934</span><span class="p">}</span>
-<span class="n">content</span><span class="o">-</span><span class="nb">type</span><span class="p">:</span> <span class="n">text</span><span class="o">/</span><span class="n">html</span>
-<span class="n">connection</span><span class="p">:</span> <span class="n">keep</span><span class="o">-</span><span class="n">alive</span>
-</pre></div>
-</div>
-<p>在返回的 header 中，<code class="docutils literal notranslate"><span class="pre">file_infos</span></code> 字段以 json 格式展示文件列表以及对应文件大小（单位字节）</p>
-</li>
-<li><p class="first">下载日志文件</p>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>curl -X GET -uuser:passwd http://fe_host:http_port/api/get_log_file?type=fe.audit.log\&file=fe.audit.log.20190528.1
-</pre></div>
-</div>
-<p>返回结果：</p>
-<p>以文件的形式下载指定的文件。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="id3">
-<h2>接口说明<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>该接口需要 admin 权限。</p>
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diff --git a/content/Docs/cn/administrator-guide/http-actions/get-label-state.html b/content/Docs/cn/administrator-guide/http-actions/get-label-state.html
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-<h1>GET LABEL STATE<a class="headerlink" href="#get-label-state" title="Permalink to this headline">¶</a></h1>
-<div class="section" id="description">
-<h2>description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>NAME:
- get_label_state: get label's state
-
-SYNOPSIS
- curl -u user:passwd http://host:port/api/{db}/{label}/_state
-
-DESCRIPTION
- 该命令用于查看一个Label对应的事务状态
-
-RETURN VALUES
- 执行完毕后，会以Json格式返回这次导入的相关内容。当前包括一下字段
- Label：本次导入的 label，如果没有指定，则为一个 uuid。
- Status：此命令是否成功执行，Success表示成功执行
- Message： 具体的执行信息
- State: 只有在Status为Success时才有意义
- UNKNOWN: 没有找到对应的Label
- PREPARE: 对应的事务已经prepare，但尚未提交
- COMMITTED: 事务已经提交，不能被cancel
- VISIBLE: 事务提交，并且数据可见，不能被cancel
- ABORTED: 事务已经被ROLLBACK，导入已经失败。
-
-ERRORS
-</pre></div>
-</div>
-</div>
-<div class="section" id="example">
-<h2>example<a class="headerlink" href="#example" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="mf">1.</span> <span class="n">获得testDb</span><span class="p">,</span> <span class="n">testLabel的状态</span>
- <span class="n">curl</span> <span class="o">-</span><span class="n">u</span> <span class="n">root</span> <span class="n">http</span><span class="p">:</span><span class="o">//</span><span class="n">host</span><span class="p">:</span><span class="n">port</span><span class="o">/</span><span class="n">api</span><span class="o">/</span><span class="n">testDb</span><span class="o">/</span><span class="n">testLabel</span><span class="o">/</span><span class="n">_state</span>
-</pre></div>
-</div>
-</div>
-<div class="section" id="keyword">
-<h2>keyword<a class="headerlink" href="#keyword" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">GET</span><span class="p">,</span> <span class="n">LABEL</span><span class="p">,</span> <span class="n">STATE</span>
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-<div class="section" id="description">
-<h2>description<a class="headerlink" href="#description" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>该功能用于恢复trash目录中被误删的tablet数据。
-
-说明：这个功能暂时只在be服务中提供一个http接口。如果要使用，
-需要向要进行数据恢复的那台be机器的http端口发送restore tablet api请求。api格式如下：
-METHOD: POST
-URI: http://be_host:be_http_port/api/restore_tablet?tablet_id=xxx&schema_hash=xxx
-</pre></div>
-</div>
-</div>
-<div class="section" id="example">
-<h2>example<a class="headerlink" href="#example" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">curl</span> <span class="o">-</span><span class="n">X</span> <span class="n">POST</span> <span class="s2">"http://hostname:8088/api/restore_tablet?tablet_id=123456\&schema_hash=1111111"</span>
-</pre></div>
-</div>
-<p>##keyword</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">RESTORE</span><span class="p">,</span><span class="n">TABLET</span><span class="p">,</span><span class="n">RESTORE</span><span class="p">,</span><span class="n">TABLET</span>
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- <div class="section" id="broker-load">
-<h1>Broker Load<a class="headerlink" href="#broker-load" title="Permalink to this headline">¶</a></h1>
-<p>Broker load 是一个异步的导入方式，支持的数据源取决于 Broker 进程支持的数据源。</p>
-<p>用户需要通过 MySQL 协议 创建 Broker load 导入，并通过查看导入命令检查导入结果。</p>
-<div class="section" id="id1">
-<h2>适用场景<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>源数据在 Broker 可以访问的存储系统中，如 HDFS。</li>
-<li>数据量在 几十到百GB 级别。</li>
-</ul>
-</div>
-<div class="section" id="id2">
-<h2>名词解释<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<ol class="simple">
-<li>Frontend（FE）：Doris 系统的元数据和调度节点。在导入流程中主要负责导入 plan 生成和导入任务的调度工作。</li>
-<li>Backend（BE）：Doris 系统的计算和存储节点。在导入流程中主要负责数据的 ETL 和存储。</li>
-<li>Broker：Broker 为一个独立的无状态进程。封装了文件系统接口，提供 Doris 读取远端存储系统中文件的能力。</li>
-<li>Plan：导入执行计划，BE 会执行导入执行计划将数据导入到 Doris 系统中。</li>
-</ol>
-</div>
-<div class="section" id="id3">
-<h2>基本原理<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>用户在提交导入任务后，FE 会生成对应的 Plan 并根据目前 BE 的个数和文件的大小，将 Plan 分给 多个 BE 执行，每个 BE 执行一部分导入数据。</p>
-<p>BE 在执行的过程中会从 Broker 拉取数据，在对数据 transform 之后将数据导入系统。所有 BE 均完成导入，由 FE 最终决定导入是否成功。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="o">+</span>
- <span class="o">|</span> <span class="mf">1.</span> <span class="n">user</span> <span class="n">create</span> <span class="n">broker</span> <span class="n">load</span>
- <span class="n">v</span>
- <span class="o">+----+----+</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="n">FE</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">+----+----+</span>
- <span class="o">|</span>
- <span class="o">|</span> <span class="mf">2.</span> <span class="n">BE</span> <span class="n">etl</span> <span class="ow">and</span> <span class="n">load</span> <span class="n">the</span> <span class="n">data</span>
- <span class="o">+--------------------------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+---</span><span class="n">v</span><span class="o">---+</span> <span class="o">+--</span><span class="n">v</span><span class="o">----+</span> <span class="o">+---</span><span class="n">v</span><span class="o">---+</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">BE</span> <span class="o">|</span> <span class="o">|</span> <span class="n">BE</span> <span class="o">|</span> <span class="o">|</span> <span class="n">BE</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+---+-^-+</span> <span class="o">+---+-^-+</span> <span class="o">+--+-^--+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="mf">3.</span> <span class="n">pull</span> <span class="n">data</span> <span class="kn">from</span> <span class="nn">broker</span>
-<span class="o">+---</span><span class="n">v</span><span class="o">-+-+</span> <span class="o">+---</span><span class="n">v</span><span class="o">-+-+</span> <span class="o">+--</span><span class="n">v</span><span class="o">-+--+</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span><span class="n">Broker</span> <span class="o">|</span> <span class="o">|</span><span class="n">Broker</span> <span class="o">|</span> <span class="o">|</span><span class="n">Broker</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+---+-^-+</span> <span class="o">+---+-^-+</span> <span class="o">+---+-^-+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+---</span><span class="n">v</span><span class="o">-+-----------</span><span class="n">v</span><span class="o">-+----------</span><span class="n">v</span><span class="o">-+-+</span>
-<span class="o">|</span> <span class="n">HDFS</span><span class="o">/</span><span class="n">BOS</span><span class="o">/</span><span class="n">AFS</span> <span class="n">cluster</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span>
-<span class="o">+----------------------------------+</span>
-</pre></div>
-</div>
-</div>
-<div class="section" id="id4">
-<h2>基本操作<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id5">
-<h3>创建导入<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<p>Broker load 创建导入语句</p>
-<p>语法：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">LOAD</span> <span class="n">LABEL</span> <span class="n">db_name</span><span class="o">.</span><span class="n">label_name</span>
-<span class="p">(</span><span class="n">data_desc</span><span class="p">,</span> <span class="o">...</span><span class="p">)</span>
-<span class="n">WITH</span> <span class="n">BROKER</span> <span class="n">broker_name</span> <span class="n">broker_properties</span>
-<span class="p">[</span><span class="n">PROPERTIES</span> <span class="p">(</span><span class="n">key1</span><span class="o">=</span><span class="n">value1</span><span class="p">,</span> <span class="o">...</span> <span class="p">)]</span>
-
-<span class="o">*</span> <span class="n">data_desc</span><span class="p">:</span>
-
- <span class="n">DATA</span> <span class="n">INFILE</span> <span class="p">(</span><span class="s1">'file_path'</span><span class="p">,</span> <span class="o">...</span><span class="p">)</span>
- <span class="p">[</span><span class="n">NEGATIVE</span><span class="p">]</span>
- <span class="n">INTO</span> <span class="n">TABLE</span> <span class="n">tbl_name</span>
- <span class="p">[</span><span class="n">PARTITION</span> <span class="p">(</span><span class="n">p1</span><span class="p">,</span> <span class="n">p2</span><span class="p">)]</span>
- <span class="p">[</span><span class="n">COLUMNS</span> <span class="n">TERMINATED</span> <span class="n">BY</span> <span class="n">separator</span> <span class="p">]</span>
- <span class="p">[(</span><span class="n">col1</span><span class="p">,</span> <span class="o">...</span><span class="p">)]</span>
- <span class="p">[</span><span class="n">SET</span> <span class="p">(</span><span class="n">k1</span><span class="o">=</span><span class="n">f1</span><span class="p">(</span><span class="n">xx</span><span class="p">),</span> <span class="n">k2</span><span class="o">=</span><span class="n">f2</span><span class="p">(</span><span class="n">xx</span><span class="p">))]</span>
-
-<span class="o">*</span> <span class="n">broker_properties</span><span class="p">:</span>
-
- <span class="p">(</span><span class="n">key1</span><span class="o">=</span><span class="n">value1</span><span class="p">,</span> <span class="o">...</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">LOAD</span> <span class="n">LABEL</span> <span class="n">db1</span><span class="o">.</span><span class="n">label1</span>
-<span class="p">(</span>
- <span class="n">DATA</span> <span class="n">INFILE</span><span class="p">(</span><span class="s2">"hdfs://abc.com:8888/user/palo/test/ml/file1"</span><span class="p">)</span>
- <span class="n">INTO</span> <span class="n">TABLE</span> <span class="n">tbl1</span>
- <span class="n">COLUMNS</span> <span class="n">TERMINATED</span> <span class="n">BY</span> <span class="s2">","</span>
- <span class="p">(</span><span class="n">tmp_c1</span><span class="p">,</span><span class="n">tmp_c2</span><span class="p">)</span>
- <span class="n">SET</span>
- <span class="p">(</span>
- <span class="nb">id</span><span class="o">=</span><span class="n">tmp_c2</span><span class="p">,</span>
- <span class="n">name</span><span class="o">=</span><span class="n">tmp_c1</span>
- <span class="p">),</span>
- <span class="n">DATA</span> <span class="n">INFILE</span><span class="p">(</span><span class="s2">"hdfs://abc.com:8888/user/palo/test/ml/file2"</span><span class="p">)</span>
- <span class="n">INTO</span> <span class="n">TABLE</span> <span class="n">tbl2</span>
- <span class="n">COLUMNS</span> <span class="n">TERMINATED</span> <span class="n">BY</span> <span class="s2">","</span>
- <span class="p">(</span><span class="n">col1</span><span class="p">,</span> <span class="n">col2</span><span class="p">)</span>
-<span class="p">)</span>
-<span class="n">WITH</span> <span class="n">BROKER</span> <span class="s1">'broker'</span>
-<span class="p">(</span>
- <span class="s2">"username"</span><span class="o">=</span><span class="s2">"user"</span><span class="p">,</span>
- <span class="s2">"password"</span><span class="o">=</span><span class="s2">"pass"</span>
-<span class="p">)</span>
-<span class="n">PROPERTIES</span>
-<span class="p">(</span>
- <span class="s2">"timeout"</span> <span class="o">=</span> <span class="s2">"3600"</span>
-<span class="p">);</span>
-</pre></div>
-</div>
-<p>创建导入的详细语法执行 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">BROKER</span> <span class="pre">LOAD</span></code> 查看语法帮助。这里主要介绍 Broker load 的创建导入语法中参数意义和注意事项。</p>
-<div class="section" id="label">
-<h4>Label<a class="headerlink" href="#label" title="Permalink to this headline">¶</a></h4>
-<p>导入任务的标识。每个导入任务，都有一个在单 database 内部唯一的 Label。Label 是用户在导入命令中自定义的名称。通过这个 Label，用户可以查看对应导入任务的执行情况。</p>
-<p>Label 的另一个作用，是防止用户重复导入相同的数据。<strong>强烈推荐用户同一批次数据使用相同的label。这样同一批次数据的重复请求只会被接受一次，保证了 At-Most-Once 语义</strong></p>
-<p>当 Label 对应的导入作业状态为 CANCELLED 时，可以再次使用该 Label 提交导入作业。</p>
-</div>
-<div class="section" id="id6">
-<h4>数据描述类参数<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h4>
-<p>数据描述类参数主要指的是 Broker load 创建导入语句中的属于 <code class="docutils literal notranslate"><span class="pre">data_desc</span></code> 部分的参数。每组 <code class="docutils literal notranslate"><span class="pre">data_desc</span> </code> 主要表述了本次导入涉及到的数据源地址，ETL 函数，目标表及分区等信息。</p>
-<p>下面主要对数据描述类的部分参数详细解释：</p>
-<ul>
-<li><p class="first">多表导入</p>
-<p>Broker load 支持一次导入任务涉及多张表，每个 Broker load 导入任务可在多个 <code class="docutils literal notranslate"><span class="pre">data_desc</span></code> 声明多张表来实现多表导入。每个单独的 <code class="docutils literal notranslate"><span class="pre">data_desc</span></code> 还可以指定属于该表的数据源地址。Broker load 保证了单次导入的多张表之间原子性成功或失败。</p>
-</li>
-<li><p class="first">negative</p>
-<p><code class="docutils literal notranslate"><span class="pre">data_desc</span></code>中还可以设置数据取反导入。这个功能主要用于，当数据表中聚合列的类型都为 SUM 类型时。如果希望撤销某一批导入的数据。则可以通过 <code class="docutils literal notranslate"><span class="pre">negative</span></code> 参数当如同一批数据。Doris 会自动为这一批数据在聚合列上数据取反，以达到消除同一批数据的功能。</p>
-</li>
-<li><p class="first">partition</p>
-<p>在 <code class="docutils literal notranslate"><span class="pre">data_desc</span></code> 中可以指定待导入表的 partition 信息，如果待导入数据不属于指定的 partition 则不会被导入。同时，不在指定 Partition 的数据会被认为是错误数据。</p>
-</li>
-<li><p class="first">set column mapping</p>
-<p>在 <code class="docutils literal notranslate"><span class="pre">data_desc</span></code> 中的 SET 语句负责设置列函数变换，这里的列函数变换支持所有查询的等值表达式变换。如果原始数据的列和表中的列不一一对应，就需要用到这个属性。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id7">
-<h4>导入作业参数<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h4>
-<p>导入作业参数主要指的是 Broker load 创建导入语句中的属于 <code class="docutils literal notranslate"><span class="pre">opt_properties</span></code>部分的参数。导入作业参数是作用于整个导入作业的。</p>
-<p>下面主要对导入作业参数的部分参数详细解释：</p>
-<ul>
-<li><p class="first">timeout</p>
-<p>导入作业的超时时间(以秒为单位)，用户可以在 <code class="docutils literal notranslate"><span class="pre">opt_properties</span></code> 中自行设置每个导入的超时时间。导入任务在设定的 timeout 时间内未完成则会被系统取消，变成 CANCELLED。Broker load 的默认导入超时时间为4小时。</p>
-<p>通常情况下，用户不需要手动设置导入任务的超时时间。当在默认超时时间内无法完成导入时，可以手动设置任务的超时时间。</p>
-<blockquote>
-<div><p>推荐超时时间</p>
-<p>总文件大小（MB） / 用户 Doris 集群最慢导入速度(MB/s) > timeout > （（总文件大小(MB) * 待导入的表及相关 Roll up 表的个数） / (10 * 导入并发数） ）</p>
-</div></blockquote>
-<blockquote>
-<div><p>导入并发数见文档最后的导入系统配置说明，公式中的 10 为目前的导入限速 10MB/s。</p>
-</div></blockquote>
-<blockquote>
-<div><p>例如一个 1G 的待导入数据，待导入表包含3个 Rollup 表，当前的导入并发数为 3。则 timeout 的 最小值为 <code class="docutils literal notranslate"><span class="pre">(1</span> <span class="pre">*</span> <span class="pre">1024</span> <span class="pre">*</span> <span class="pre">3</span> <span class="pre">)</span> <span class="pre">/</span> <span class="pre">(10</span> <span class="pre">*</span> <span class="pre">3)</span> <span class="pre">=</span> <span class="pre">102</span> <span class="pre">秒</span></code></p>
-</div></blockquote>
-<p>由于每个 Doris 集群的机器环境不同且集群并发的查询任务也不同，所以用户 Doris 集群的最慢导入速度需要用户自己根据历史的导入任务速度进行推测。</p>
-</li>
-<li><p class="first">max_filter_ratio</p>
-<p>导入任务的最大容忍率，默认为0容忍，取值范围是0~1。当导入的错误率超过该值，则导入失败。</p>
-<p>如果用户希望忽略错误的行，可以通过设置这个参数大于 0，来保证导入可以成功。</p>
-<p>计算公式为：</p>
-<p><code class="docutils literal notranslate"><span class="pre">(dpp.abnorm.ALL</span> <span class="pre">/</span> <span class="pre">(dpp.abnorm.ALL</span> <span class="pre">+</span> <span class="pre">dpp.norm.ALL</span> <span class="pre">)</span> <span class="pre">)</span> <span class="pre">></span> <span class="pre">max_filter_ratio</span></code></p>
-<p><code class="docutils literal notranslate"><span class="pre">dpp.abnorm.ALL</span></code> 表示数据质量不合格的行数。如类型不匹配，列数不匹配，长度不匹配等等。</p>
-<p><code class="docutils literal notranslate"><span class="pre">dpp.norm.ALL</span></code> 指的是导入过程中正确数据的条数。可以通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">LOAD</span></code> 命令查询导入任务的正确数据量。</p>
-<p>原始文件的行数 = <code class="docutils literal notranslate"><span class="pre">dpp.abnorm.ALL</span> <span class="pre">+</span> <span class="pre">dpp.norm.ALL</span></code></p>
-</li>
-<li><p class="first">exec_mem_limit</p>
-<p>导入任务的内存使用上限。当导入任务使用的内存超过设定上限时，导入任务会被 CANCEL。默认为 2G，单位为字节。</p>
-<p>当导入出现 <code class="docutils literal notranslate"><span class="pre">Memory</span> <span class="pre">exceed</span> <span class="pre">limit</span></code> 错误时，可以适当调整这个参数，如调整为 4G、8G 等。</p>
-</li>
-<li><p class="first">strict_mode</p>
-<p>Broker load 导入可以开启 strict mode 模式。开启方式为 <code class="docutils literal notranslate"><span class="pre">properties</span> <span class="pre">("strict_mode"</span> <span class="pre">=</span> <span class="pre">"true")</span></code> 。默认的 strict mode 为开启。</p>
-<p>strict mode 模式的意思是：对于导入过程中的列类型转换进行严格过滤。严格过滤的策略如下：</p>
-<ol class="simple">
-<li>对于列类型转换来说，如果 strict mode 为true，则错误的数据将被 filter。这里的错误数据是指：原始数据并不为空值，在参与列类型转换后结果为空值的这一类数据。</li>
-<li>对于导入的某列由函数变换生成时，strict mode 对其不产生影响。</li>
-<li>对于导入的某列类型包含范围限制的，如果原始数据能正常通过类型转换，但无法通过范围限制的，strict mode 对其也不产生影响。例如：如果类型是 decimal(1,0), 原始数据为 10，则属于可以通过类型转换但不在列声明的范围内。这种数据 strict 对其不产生影响。</li>
-</ol>
-</li>
-</ul>
-</div>
-<div class="section" id="strict-mode-source-data">
-<h4>strict mode 与 source data 的导入关系<a class="headerlink" href="#strict-mode-source-data" title="Permalink to this headline">¶</a></h4>
-<p>这里以列类型为 TinyInt 来举例</p>
-<blockquote>
-<div>注：当表中的列允许导入空值时</div></blockquote>
-<table border="1" class="docutils">
-<thead>
-<tr>
-<th>source data</th>
-<th>source data example</th>
-<th>string to int</th>
-<th>strict_mode</th>
-<th>result</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td>空值</td>
-<td>\N</td>
-<td>N/A</td>
-<td>true or false</td>
-<td>NULL</td>
-</tr>
-<tr>
-<td>not null</td>
-<td>aaa or 2000</td>
-<td>NULL</td>
-<td>true</td>
-<td>invalid data(filtered)</td>
-</tr>
-<tr>
-<td>not null</td>
-<td>aaa</td>
-<td>NULL</td>
-<td>false</td>
-<td>NULL</td>
-</tr>
-<tr>
-<td>not null</td>
-<td>1</td>
-<td>1</td>
-<td>true or false</td>
-<td>correct data</td>
-</tr>
-</tbody>
-</table><p>这里以列类型为 Decimal(1,0) 举例</p>
-<blockquote>
-<div>注：当表中的列允许导入空值时</div></blockquote>
-<table border="1" class="docutils">
-<thead>
-<tr>
-<th>source data</th>
-<th>source data example</th>
-<th>string to int</th>
-<th>strict_mode</th>
-<th>result</th>
-</tr>
-</thead>
-<tbody>
-<tr>
-<td>空值</td>
-<td>\N</td>
-<td>N/A</td>
-<td>true or false</td>
-<td>NULL</td>
-</tr>
-<tr>
-<td>not null</td>
-<td>aaa</td>
-<td>NULL</td>
-<td>true</td>
-<td>invalid data(filtered)</td>
-</tr>
-<tr>
-<td>not null</td>
-<td>aaa</td>
-<td>NULL</td>
-<td>false</td>
-<td>NULL</td>
-</tr>
-<tr>
-<td>not null</td>
-<td>1 or 10</td>
-<td>1</td>
-<td>true or false</td>
-<td>correct data</td>
-</tr>
-</tbody>
-</table><blockquote>
-<div>注意：10 虽然是一个超过范围的值，但是因为其类型符合 decimal的要求，所以 strict mode对其不产生影响。10 最后会在其他 ETL 处理流程中被过滤。但不会被 strict mode 过滤。</div></blockquote>
-</div>
-</div>
-<div class="section" id="id8">
-<h3>查看导入<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
-<p>Broker load 导入方式由于是异步的，所以用户必须将创建导入的 Label 记录，并且在<strong>查看导入命令中使用 Label 来查看导入结果</strong>。查看导入命令在所有导入方式中是通用的，具体语法可执行 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">SHOW</span> <span class="pre">LOAD</span></code> 查看。</p>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>mysql> show load order by createtime desc limit 1\G
-*************************** 1. row ***************************
- JobId: 76391
- Label: label1
- State: FINISHED
- Progress: ETL:N/A; LOAD:100%
- Type: BROKER
- EtlInfo: dpp.abnorm.ALL=15; dpp.norm.ALL=28133376
- TaskInfo: cluster:N/A; timeout(s):10800; max_filter_ratio:5.0E-5
- ErrorMsg: N/A
- CreateTime: 2019-07-27 11:46:42
- EtlStartTime: 2019-07-27 11:46:44
- EtlFinishTime: 2019-07-27 11:46:44
- LoadStartTime: 2019-07-27 11:46:44
-LoadFinishTime: 2019-07-27 11:50:16
- URL: http://192.168.1.1:8040/api/_load_error_log?file=__shard_4/error_log_insert_stmt_4bb00753932c491a-a6da6e2725415317_4bb00753932c491a_a6da6e2725415317
-</pre></div>
-</div>
-<p>下面主要介绍了查看导入命令返回结果集中参数意义：</p>
-<ul>
-<li><p class="first">JobId</p>
-<p>导入任务的唯一ID，每个导入任务的 JobId 都不同，有系统自动生成。与 Label 不同的是，JobId永远不会相同，而 Label 则可以在导入任务失败后被复用。</p>
-</li>
-<li><p class="first">Label</p>
-<p>导入任务的标识。</p>
-</li>
-<li><p class="first">State</p>
-<p>导入任务当前所处的阶段。在 Broker load 导入过程中主要会出现 PENDING 和 LOADING 这两个导入中的状态。如果 Broker load 处于 PENDING 状态，则说明当前导入任务正在等待被执行；LOADING 状态则表示正在执行中。</p>
-<p>导入任务的最终阶段有两个：CANCELLED 和 FINISHED，当 Load job 处于这两个阶段时，导入完成。其中 CANCELLED 为导入失败，FINISHED 为导入成功。</p>
-</li>
-<li><p class="first">Progress</p>
-<p>导入任务的进度描述。分为两种进度：ETL 和 LOAD，对应了导入流程的两个阶段 ETL 和 LOADING。目前 Broker load 由于只有 LOADING 阶段，所以 ETL 则会永远显示为 <code class="docutils literal notranslate"><span class="pre">N/A</span></code></p>
-<p>LOAD 的进度范围为：0~100%。</p>
-<p><code class="docutils literal notranslate"><span class="pre">LOAD</span> <span class="pre">进度</span> <span class="pre">=</span> <span class="pre">当前完成导入的表个数</span> <span class="pre">/</span> <span class="pre">本次导入任务设计的总表个数</span> <span class="pre">*</span> <span class="pre">100%</span></code></p>
-<p><strong>如果所有导入表均完成导入，此时 LOAD 的进度为 99%</strong> 导入进入到最后生效阶段，整个导入完成后，LOAD 的进度才会改为 100%。</p>
-<p>导入进度并不是线性的。所以如果一段时间内进度没有变化，并不代表导入没有在执行。</p>
-</li>
-<li><p class="first">Type</p>
-<p>导入任务的类型。Broker load 的 type 取值只有 BROKER。</p>
-</li>
-<li><p class="first">EtlInfo</p>
-<p>主要显示了导入的数据量指标 <code class="docutils literal notranslate"><span class="pre">dpp.norm.ALL</span> <span class="pre">和</span> <span class="pre">dpp.abnorm.ALL</span></code>。用户可以根据这两个指标验证当前导入任务的错误率是否超过 max_filter_ratio。</p>
-</li>
-<li><p class="first">TaskInfo</p>
-<p>主要显示了当前导入任务参数，也就是创建 Broker load 导入任务时用户指定的导入任务参数，包括：<code class="docutils literal notranslate"><span class="pre">cluster</span></code>，<code class="docutils literal notranslate"><span class="pre">timeout</span></code> 和<code class="docutils literal notranslate"><span class="pre">max_filter_ratio</span></code>。</p>
-</li>
-<li><p class="first">ErrorMsg</p>
-<p>在导入任务状态为CANCELLED，会显示失败的原因，显示分两部分：type 和 msg，如果导入任务成功则显示 <code class="docutils literal notranslate"><span class="pre">N/A</span></code>。</p>
-<p>type的取值意义：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>USER_CANCEL: 用户取消的任务
-ETL_RUN_FAIL：在ETL阶段失败的导入任务
-ETL_QUALITY_UNSATISFIED：数据质量不合格，也就是错误数据率超过了 max_filter_ratio
-LOAD_RUN_FAIL：在LOADING阶段失败的导入任务
-TIMEOUT：导入任务没在超时时间内完成
-UNKNOWN：未知的导入错误
-</pre></div>
-</div>
-</li>
-<li><p class="first">CreateTime/EtlStartTime/EtlFinishTime/LoadStartTime/LoadFinishTime</p>
-<p>这几个值分别代表导入创建的时间，ETL阶段开始的时间，ETL阶段完成的时间，Loading阶段开始的时间和整个导入任务完成的时间。</p>
-<p>Broker load 导入由于没有 ETL 阶段，所以其 EtlStartTime, EtlFinishTime, LoadStartTime 被设置为同一个值。</p>
-<p>导入任务长时间停留在 CreateTime，而 LoadStartTime 为 N/A 则说明目前导入任务堆积严重。用户可减少导入提交的频率。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">LoadFinishTime</span> <span class="o">-</span> <span class="n">CreateTime</span> <span class="o">=</span> <span class="n">整个导入任务所消耗时间</span>
-<span class="n">LoadFinishTime</span> <span class="o">-</span> <span class="n">LoadStartTime</span> <span class="o">=</span> <span class="n">整个</span> <span class="n">Broker</span> <span class="n">load</span> <span class="n">导入任务执行时间</span> <span class="o">=</span> <span class="n">整个导入任务所消耗时间</span> <span class="o">-</span> <span class="n">导入任务等待的时间</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">URL</p>
-<p>导入任务的错误数据样例，访问 URL 地址既可获取本次导入的错误数据样例。当本次导入不存在错误数据时，URL 字段则为 N/A。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id9">
-<h3>取消导入<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h3>
-<p>当 Broker load 作业状态不为 CANCELLED 或 FINISHED 时，可以被用户手动取消。取消时需要指定待取消导入任务的 Label 。取消导入命令语法可执行 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">CANCEL</span> <span class="pre">LOAD</span></code>查看。</p>
-</div>
-</div>
-<div class="section" id="id10">
-<h2>相关系统配置<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE 配置<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<p>下面几个配置属于 Broker load 的系统级别配置，也就是作用于所有 Broker load 导入任务的配置。主要通过修改 <code class="docutils literal notranslate"> <span class="pre">fe.conf</span></code>来调整配置值。</p>
-<ul>
-<li><p class="first">min_bytes_per_broker_scanner/max_bytes_per_broker_scanner/max_broker_concurrency</p>
-<p>前两个配置限制了单个 BE 处理的数据量的最小和最大值。第三个配置限制了一个作业的最大的导入并发数。最小处理的数据量，最大并发数，源文件的大小和当前集群 BE 的个数 <strong>共同决定了本次导入的并发数</strong>。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>本次导入并发数 = Math.min(源文件大小/最小处理量，最大并发数，当前BE节点个数)
-本次导入单个BE的处理量 = 源文件大小/本次导入的并发数
-</pre></div>
-</div>
-<p>通常一个导入作业支持的最大数据量为 <code class="docutils literal notranslate"><span class="pre">max_bytes_per_broker_scanner</span> <span class="pre">*</span> <span class="pre">BE</span> <span class="pre">节点数</span></code>。如果需要导入更大数据量，则需要适当调整 <code class="docutils literal notranslate"><span class="pre">max_bytes_per_broker_scanner</span></code> 参数的大小。</p>
-<p>默认配置：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>参数名：min_bytes_per_broker_scanner， 默认 64MB，单位bytes。
-参数名：max_broker_concurrency， 默认 10。
-参数名：max_bytes_per_broker_scanner，默认 3G，单位bytes。
-</pre></div>
-</div>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id11">
-<h2>最佳实践<a class="headerlink" href="#id11" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id12">
-<h3>应用场景<a class="headerlink" href="#id12" title="Permalink to this headline">¶</a></h3>
-<p>使用 Broker load 最适合的场景就是原始数据在文件系统（HDFS，BOS，AFS）中的场景。其次，由于 Broker load 是单次导入中唯一的一种异步导入的方式，所以如果用户在导入大文件中，需要使用异步接入，也可以考虑使用 Broker load。</p>
-</div>
-<div class="section" id="id13">
-<h3>数据量<a class="headerlink" href="#id13" title="Permalink to this headline">¶</a></h3>
-<p>这里仅讨论单个 BE 的情况，如果用户集群有多个 BE 则下面标题中的数据量应该乘以 BE 个数来计算。比如：如果用户有3个 BE，则 3G 以下（包含）则应该乘以 3，也就是 9G 以下（包含）。</p>
-<ul>
-<li><p class="first">3G 以下（包含）</p>
-<p>用户可以直接提交 Broker load 创建导入请求。</p>
-</li>
-<li><p class="first">3G 以上</p>
-<p>由于单个导入 BE 最大的处理量为 3G，超过 3G 的待导入文件就需要通过调整 Broker load 的导入参数来实现大文件的导入。</p>
-<ol>
-<li><p class="first">根据当前 BE 的个数和原始文件的大小修改单个 BE 的最大扫描量和最大并发数。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>修改 fe.conf 中配置
-
-max_broker_concurrency = BE 个数
-当前导入任务单个 BE 处理的数据量 = 原始文件大小 / max_broker_concurrency
-max_bytes_per_broker_scanner >= 当前导入任务单个 BE 处理的数据量
-
-比如一个 100G 的文件，集群的 BE 个数为 10 个
-max_broker_concurrency = 10
-max_bytes_per_broker_scanner >= 10G = 100G / 10
-</pre></div>
-</div>
-<p>修改后，所有的 BE 会并发的处理导入任务，每个 BE 处理原始文件的一部分。</p>
-<p><em>注意：上述两个 FE 中的配置均为系统配置，也就是说其修改是作用于所有的 Broker load的任务的。</em></p>
-</li>
-<li><p class="first">在创建导入的时候自定义当前导入任务的 timeout 时间</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>当前导入任务单个 BE 处理的数据量 / 用户 Doris 集群最慢导入速度(MB/s) >= 当前导入任务的 timeout 时间 >= 当前导入任务单个 BE 处理的数据量 / 10M/s
-
-比如一个 100G 的文件，集群的 BE 个数为 10个
-timeout >= 1000s = 10G / 10M/s
-</pre></div>
-</div>
-</li>
-<li><p class="first">当用户发现第二步计算出的 timeout 时间超过系统默认的导入最大超时时间 4小时</p>
-<p>这时候不推荐用户将导入最大超时时间直接改大来解决问题。单个导入时间如果超过默认的导入最大超时时间4小时，最好是通过切分待导入文件并且分多次导入来解决问题。主要原因是：单次导入超过4小时的话，导入失败后重试的时间成本很高。</p>
-<p>可以通过如下公式计算出 Doris 集群期望最大导入文件数据量：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>期望最大导入文件数据量 = 14400s * 10M/s * BE 个数
-比如：集群的 BE 个数为 10个
-期望最大导入文件数据量 = 14400 * 10M/s * 10 = 1440000M ≈ 1440G
-
-注意：一般用户的环境可能达不到 10M/s 的速度，所以建议超过 500G 的文件都进行文件切分，再导入。
-</pre></div>
-</div>
-</li>
-</ol>
-</li>
-</ul>
-</div>
-<div class="section" id="id14">
-<h3>完整例子<a class="headerlink" href="#id14" title="Permalink to this headline">¶</a></h3>
-<p>数据情况：用户数据在 HDFS 中，文件地址为 hdfs://abc.com:8888/store_sales, hdfs 的认证用户名为 root, 密码为 password, 数据量大小约为 30G，希望导入到数据库 bj_sales 的表 store_sales 中。</p>
-<p>集群情况：集群的 BE 个数约为 3 个，Broker 名称均为 broker。</p>
-<ul>
-<li><p class="first">step1: 经过上述方法的计算，本次导入的单个 BE 导入量为 10G，则需要先修改 FE 的配置，将单个 BE 导入最大量修改为：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">max_bytes_per_broker_scanner</span> <span class="o">=</span> <span class="mi">10737418240</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">step2: 经计算，本次导入的时间大约为 1000s，并未超过默认超时时间，可不配置导入自定义超时时间。</p>
-</li>
-<li><p class="first">step3：创建导入语句</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">LOAD</span> <span class="n">LABEL</span> <span class="n">bj_sales</span><span class="o">.</span><span class="n">store_sales_broker_load_01</span>
-<span class="p">(</span>
- <span class="n">DATA</span> <span class="n">INFILE</span><span class="p">(</span><span class="s2">"hdfs://abc.com:8888/store_sales"</span><span class="p">)</span>
- <span class="n">INTO</span> <span class="n">TABLE</span> <span class="n">store_sales</span>
-<span class="p">)</span>
-<span class="n">WITH</span> <span class="n">BROKER</span> <span class="s1">'broker'</span>
-<span class="p">(</span><span class="s2">"username"</span><span class="o">=</span><span class="s2">"root"</span><span class="p">,</span> <span class="s2">"password"</span><span class="o">=</span><span class="s2">"password"</span><span class="p">);</span>
-</pre></div>
-</div>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id15">
-<h2>常见问题<a class="headerlink" href="#id15" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">导入报错：<code class="docutils literal notranslate"><span class="pre">Scan</span> <span class="pre">bytes</span> <span class="pre">per</span> <span class="pre">broker</span> <span class="pre">scanner</span> <span class="pre">exceed</span> <span class="pre">limit:xxx</span></code></p>
-<p>请参照文档中最佳实践部分，修改 FE 配置项 <code class="docutils literal notranslate"><span class="pre">max_bytes_per_broker_scanner</span></code> 和 <code class="docutils literal notranslate"><span class="pre">max_broker_concurrency</span></code></p>
-</li>
-<li><p class="first">导入报错：<code class="docutils literal notranslate"><span class="pre">failed</span> <span class="pre">to</span> <span class="pre">send</span> <span class="pre">batch</span></code> 或 <code class="docutils literal notranslate"><span class="pre">TabletWriter</span> <span class="pre">add</span> <span class="pre">batch</span> <span class="pre">with</span> <span class="pre">unknown</span> <span class="pre">id</span></code></p>
-<p>请参照 <a class="reference internal" href="load-manual.html"><span class="doc">导入手册</span></a> 中 <strong>通用系统配置</strong> 中 <strong>BE 配置</strong>，适当修改 <code class="docutils literal notranslate"><span class="pre">tablet_writer_rpc_timeout_sec</span></code> 和 <code class="docutils literal notranslate"><span class="pre">streaming_load_rpc_max_alive_time_sec</span></code>。</p>
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- <div class="section" id="insert-into">
-<h1>Insert Into<a class="headerlink" href="#insert-into" title="Permalink to this headline">¶</a></h1>
-<p>Insert Into 语句的使用方式和 MySQL 等数据库中 Insert Into 语句的使用方式类似。但在 Doris 中，所有的数据写入都是一个独立的导入作业。所以这里将 Insert Into 也作为一种导入方式介绍。</p>
-<p>主要的 Insert Into 命令包含以下两种；</p>
-<ul class="simple">
-<li>INSERT INTO tbl SELECT …</li>
-<li>INSERT INTO tbl (col1, col2, …) VALUES (1, 2, …), (1,3, …);</li>
-</ul>
-<p>其中第二种命令仅用于 Demo，不要使用在测试或生产环境中。</p>
-<div class="section" id="id1">
-<h2>基本操作<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id2">
-<h3>创建导入<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h3>
-<p>Insert Into 命令需要通过 MySQL 协议提交，创建导入请求会同步返回导入结果。</p>
-<p>语法：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">INSERT</span> <span class="n">INTO</span> <span class="n">table_name</span> <span class="p">[</span><span class="n">partition_info</span><span class="p">]</span> <span class="p">[</span><span class="n">col_list</span><span class="p">]</span> <span class="p">[</span><span class="n">query_stmt</span><span class="p">]</span> <span class="p">[</span><span class="n">VALUES</span><span class="p" [...]
-</pre></div>
-</div>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">INSERT</span> <span class="n">INTO</span> <span class="n">tbl2</span> <span class="n">SELECT</span> <span class="o">*</span> <span class="n">FROM</span> <span class="n">tbl3</span><span class="p">;</span>
-<span class="n">INSERT</span> <span class="n">INTO</span> <span class="n">tbl1</span> <span class="n">VALUES</span> <span class="p">(</span><span class="s2">"qweasdzxcqweasdzxc"</span><span class="p">),</span> <span class="p">(</span><span class="s2">"a"</span><span class="p">);</span>
-</pre></div>
-</div>
-<p>下面主要介绍创建导入语句中使用到的参数：</p>
-<ul>
-<li><p class="first">partition_info</p>
-<p>导入表的目标分区，如果指定目标分区，则只会导入符合目标分区的数据。如果没有指定，则默认值为这张表的所有分区。</p>
-</li>
-<li><p class="first">col_list</p>
-<p>导入表的目标列，可以以任意的顺序存在。如果没有指定目标列，那么默认值是这张表的所有列。如果待表中的某个列没有存在目标列中，那么这个列需要有默认值，否则 Insert Into 就会执行失败。</p>
-<p>如果查询语句的结果列类型与目标列的类型不一致，那么会调用隐式类型转化，如果不能够进行转化，那么 Insert Into 语句会报语法解析错误。</p>
-</li>
-<li><p class="first">query_stmt</p>
-<p>通过一个查询语句，将查询语句的结果导入到 Doris 系统中的其他表。查询语句支持任意 Doris 支持的 SQL 查询语法。</p>
-</li>
-<li><p class="first">VALUES</p>
-<p>用户可以通过 VALUES 语法插入一条或者多条数据。</p>
-<p><em>注意：VALUES 方式仅适用于导入几条数据作为导入 DEMO 的情况，完全不适用于任何测试和生产环境。Doris 系统本身也不适合单条数据导入的场景。建议使用 INSERT INTO SELECT 的方式进行批量导入。</em></p>
-</li>
-</ul>
-</div>
-<div class="section" id="id3">
-<h3>导入结果<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h3>
-<p>Insert Into 本身就是一个 SQL 命令，所以返回的行为同 SQL 命令的返回行为。</p>
-<p>如果导入失败，则返回语句执行失败。如果导入成功，则返回语句执行成功，还会附加返回一个 Label 字段。</p>
-<p>Label 是该 Insert Into 导入作业的标识。每个导入作业，都有一个在单 database 内部唯一的 Label。Insert Into 的 Label 则是由系统生成的，用户可以拿着这个 Label 通过查询导入命令异步获取导入状态。</p>
-</div>
-</div>
-<div class="section" id="id4">
-<h2>相关系统配置<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE 配置<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<ul>
-<li><p class="first">timeout</p>
-<p>导入任务的超时时间(以秒为单位)，导入任务在设定的 timeout 时间内未完成则会被系统取消，变成 CANCELLED。</p>
-<p>目前 Insert Into 并不支持自定义导入的 timeout 时间，所有 Insert Into 导入的超时时间是统一的，默认的 timeout 时间为1小时。如果导入的源文件无法再规定时间内完成导入，则需要调整 FE 的参数<code class="docutils literal notranslate"><span class="pre">insert_load_default_timeout_second</span></code>。</p>
-<p>同时 Insert Into 语句收到 Session 变量 <code class="docutils literal notranslate"><span class="pre">query_timeout</span></code> 的限制。可以通过 <code class="docutils literal notranslate"><span class="pre">SET</span> <span class="pre">query_timeout</span> <span class="pre">=</span> <span class="pre">xxx;</span></code> 来增加超时时间，单位是秒。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="session">
-<h3>Session 变量<a class="headerlink" href="#session" title="Permalink to this headline">¶</a></h3>
-<ul>
-<li><p class="first">enable_insert_strict</p>
-<p>Insert Into 导入本身不能控制导入可容忍的错误率。用户只能通过 <code class="docutils literal notranslate"><span class="pre">enable_insert_strict</span></code> 这个 Session 参数用来控制。当该参数设置为 false 时，表示至少有一条数据被正确导入，则返回成功。当该参数设置为 false 时，表示如果有一条数据错误，则导入失败。默认为 false。可通过 <code class="docutils literal notranslate"><span class="pre">SET</span> <span class="pre">enable_insert_strict</span> <span class="pre">=</span> <span class="pre">true;</span></code> 来设置。</p>
-</li>
-<li><p class="first">query_timeout</p>
-<p>Insert Into 本身也是一个 SQL 命令，因此 Insert Into 语句也受到 Session 变量 <code class="docutils literal notranslate"><span class="pre">query_timeout</span></code> 的限制。可以通过 <code class="docutils literal notranslate"><span class="pre">SET</span> <span class="pre">query_timeout</span> <span class="pre">=</span> <span class="pre">xxx;</span></code> 来增加超时时间，单位是秒。</p>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id5">
-<h2>最佳实践<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id6">
-<h3>应用场景<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h3>
-<ol class="simple">
-<li>用户希望仅导入几条假数据，验证一下 Doris 系统的功能。此时适合使用 INSERT INTO VALUS 的语法。</li>
-<li>用户希望将已经在 Doris 表中的数据进行 ETL 转换并导入到一个新的 Doris 表中，此时适合使用 INSERT INTO SELECT 语法。</li>
-<li>用户可以创建一种外部表，如 MySQL 外部表映射一张 MySQL 系统中的表。或者创建 Broker 外部表来映射 HDFS 上的数据文件。然后通过 INSERT INTO SELECT 语法将外部表中的数据导入到 Doris 表中存储。</li>
-</ol>
-</div>
-<div class="section" id="id7">
-<h3>数据量<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h3>
-<p>Insert Into 对数据量没有限制，大数据量导入也可以支持。但 Insert Into 有默认的超时时间，用户预估的导入数据量过大，就需要修改系统的 Insert Into 导入超时时间。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>导入数据量 = 36G 约≤ 3600s * 10M/s
-其中 10M/s 是最大导入限速，用户需要根据当前集群情况计算出平均的导入速度来替换公式中的 10M/s
-</pre></div>
-</div>
-</div>
-<div class="section" id="id8">
-<h3>完整例子<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
-<p>用户有一张表 store_sales 在数据库 sales 中，用户又创建了一张表叫 bj_store_sales 也在数据库 sales 中，用户希望将 store_sales 中销售记录在 bj 的数据导入到这张新建的表 bj_store_sales 中。导入的数据量约为：10G。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>store_sales schema：
-(id, total, user_id, sale_timestamp, region)
-
-bj_store_sales schema:
-(id, total, user_id, sale_timestamp)
-</pre></div>
-</div>
-<p>集群情况：用户当前集群的平均导入速度约为 5M/s</p>
-<ul>
-<li><p class="first">Step1: 判断是否要修改 Insert Into 的默认超时时间</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">计算导入的大概时间</span>
-<span class="mi">10</span><span class="n">G</span> <span class="o">/</span> <span class="mi">5</span><span class="n">M</span><span class="o">/</span><span class="n">s</span> <span class="o">=</span> <span class="mi">2000</span><span class="n">s</span>
-
-<span class="n">修改</span> <span class="n">FE</span> <span class="n">配置</span>
-<span class="n">insert_load_default_timeout_second</span> <span class="o">=</span> <span class="mi">2000</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">Step2：创建导入任务</p>
-<p>由于用户是希望将一张表中的数据做 ETL 并导入到目标表中，所以应该使用 Insert into query_stmt 方式导入。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">INSERT</span> <span class="n">INTO</span> <span class="n">bj_store_sales</span> <span class="n">SELECT</span> <span class="nb">id</span><span class="p">,</span> <span class="n">total</span><span class="p">,</span> <span class="n">user_id</span><span class="p">,</span> <span class="n">sale_timestamp</span> <span class="n">FROM</span> <span class="n">store_sales</span> <span class="n">where< [...]
-</pre></div>
-</div>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id9">
-<h2>常见问题<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">查看错误行</p>
-<p>由于 Insert Into 无法控制错误率，只能通过 <code class="docutils literal notranslate"><span class="pre">enable_insert_strict</span></code> 设置为完全容忍错误数据或完全忽略错误数据。因此如果 <code class="docutils literal notranslate"><span class="pre">enable_insert_strict</span></code> 设为 true，则 Insert Into 可能会失败。而如果 <code class="docutils literal notranslate"><span class="pre">enable_insert_strict</span></code> 设为 false，则可能出现仅导入了部分合格数据的情况。但无论以上哪种情况，Doris 目前无法提供查看不合格数据行的功能。因此用户无法通过 Insert Into 语句来查看具体的导入错误。</p>
-<p>错误的原因通常如：源数据列长度超过目的数据列长度、列类型不匹配、分区不匹配、列顺序不匹配等等。当依然无法检查出问题时。目前只能建议先运行 Insert Into 语句中的 SELECT 命令将数据导出到一个文件中，然后在通过 Stream load 的方式导入这个文件，来查看具体的错误。</p>
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-<li class="toctree-l4"><a class="reference internal" href="#id3">导入方式</a></li>
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- <div class="section" id="id1">
-<h1>导入总览<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h1>
-<p>导入（Load）功能就是将用户的原始数据导入到 Doris 中。导入成功后，用户即可通过 Mysql 客户端查询数据。</p>
-<p>Doris 支持多种导入方式。建议先完整阅读本文档，再根据所选择的导入方式，查看各自导入方式的详细文档。</p>
-<div class="section" id="id2">
-<h2>基本概念<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<ol class="simple">
-<li>Frontend（FE）：Doris 系统的元数据和调度节点。在导入流程中主要负责导入规划生成和导入任务的调度工作。</li>
-<li>Backend（BE）：Doris 系统的计算和存储节点。在导入流程中主要负责数据的 ETL 和存储。</li>
-<li>Broker：Broker 为一个独立的无状态进程。封装了文件系统接口，提供 Doris 读取远端存储系统中文件的能力。</li>
-<li>导入作业（Load job）：导入作业读取用户提交的源数据，转换或清洗后，将数据导入到 Doris 系统中。导入完成后，数据即可被用户查询到。</li>
-<li>Label：所有导入作业都有一个 Label。Label 在一个数据库内唯一，可由用户指定或系统自动生成，用于标识一个导入作业。相同的 Label 仅可用于一个成功的导入作业。</li>
-<li>MySQL 协议/HTTP 协议：Doris 提供两种访问协议接口。 MySQL 协议和 HTTP 协议。部分导入方式使用 MySQL 协议接口提交作业，部分导入方式使用 HTTP 协议接口提交作业。</li>
-</ol>
-</div>
-<div class="section" id="id3">
-<h2>导入方式<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>为适配不同的数据导入需求，Doris 系统提供了5种不同的导入方式。每种导入方式支持不同的数据源，存在不同的使用方式（异步，同步）。</p>
-<p>所有导入方式都支持 csv 数据格式。其中 Broker load 还支持 parquet 数据格式。</p>
-<p>每个导入方式的说明请参阅单个导入方式的操作手册。</p>
-<ul>
-<li><p class="first">Broker load</p>
-<p>通过 Broker 进程访问并读取外部数据源（如 HDFS）导入到 Doris。用户通过 Mysql 协议提交导入作业后，异步执行。通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">LOAD</span></code> 命令查看导入结果。</p>
-</li>
-<li><p class="first">Stream load</p>
-<p>用户通过 HTTP 协议提交请求并携带原始数据创建导入。主要用于快速将本地文件或数据流中的数据导入到 Doris。导入命令同步返回导入结果。</p>
-</li>
-<li><p class="first">Insert</p>
-<p>类似 MySQL 中的 Insert 语句，Doris 提供 <code class="docutils literal notranslate"><span class="pre">INSERT</span> <span class="pre">INTO</span> <span class="pre">tbl</span> <span class="pre">SELECT</span> <span class="pre">...;</span></code> 的方式从 Doris 的表中读取数据并导入到另一张表。或者通过 <code class="docutils literal notranslate"><span class="pre">INSERT</span> <span class="pre">INTO</span> <span class="pre">tbl</span> <span class="pre">VALUES(...);</span></code> 插入单条数据。</p>
-</li>
-<li><p class="first">Multi load</p>
-<p>用户通过 HTTP 协议提交多个导入作业。Multi Load 可以保证多个导入作业的原子生效。</p>
-</li>
-<li><p class="first">Routine load</p>
-<p>用户通过 MySQL 协议提交例行导入作业，生成一个常驻线程，不间断的从数据源（如 Kafka）中读取数据并导入到 Doris 中。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id4">
-<h2>基本原理<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id5">
-<h3>导入执行流程<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">+---------+</span> <span class="o">+---------+</span> <span class="o">+----------+</span> <span class="o">+-----------+</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="n">PENDING</span> <span class="o">+----->+</span> <span class="n">ETL</span> <span class="o">+----->+</span> <span class="n">LOADING</span> <span class="o">+----->+</span> <span class="n">FINISHED</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+---------+</span> <span class="o">+---+-----+</span> <span class="o">+----+-----+</span> <span class="o">+-----------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">+-----------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">+---------------+-----------------+------------></span> <span class="n">CANCELLED</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">+-----------+</span>
-</pre></div>
-</div>
-<p>如上图，一个导入作业主要经过上面4个阶段。</p>
-<ul class="simple">
-<li>PENDING（非必须）: 该阶段只有 Broker Load 才有。Broker Load 被用户提交后会短暂停留在这个阶段，直到被 FE 中的 Scheduler 调度。 其中 Scheduler 的调度间隔为5秒。</li>
-<li>ETL（非必须）： 该阶段在版本 0.10.0(包含) 之前存在，主要是用于将原始数据按照用户声明的方式进行变换，并且过滤不满足条件的原始数据。在 0.10.0 后的版本，ETL 阶段不再存在，其中数据 transform 的工作被合并到 LOADING 阶段。</li>
-<li>LOADING： 该阶段在版本 0.10.0（包含）之前主要用于将变换后的数据推到对应的 BE 存储中。在 0.10.0 后的版本，该阶段先对数据进行清洗和变换，然后将数据发送到 BE 存储中。当所有导入数据均完成导入后，进入等待生效过程，此时 Load job 依旧是 LOADING。</li>
-<li>FINISHED： 在 Load job 涉及的所有数据均生效后，Load job 的状态变成 FINISHED。FINISHED 后导入的数据均可查询。</li>
-<li>CANCELLED: 在作业 FINISH 的之前，作业都可能被取消并进入 CANCELLED 状态。如用户手动取消，或导入出现错误等。CANCELLED 也是 Load Job 的最终状态，不可被再次执行。</li>
-</ul>
-<p>上述阶段，除了 PENDING 到 LOADING 阶段是 Scheduler 轮训调度的，其他阶段之前的转移都是回调机制实现。</p>
-</div>
-<div class="section" id="label">
-<h3>Label 和 原子性<a class="headerlink" href="#label" title="Permalink to this headline">¶</a></h3>
-<p>Doris 对所有导入方式提供原子性保证。既保证同一个导入作业内的数据，原子生效。不会出现仅导入部分数据的情况。</p>
-<p>同时，每一个导入作业都有一个由用户指定或者系统自动生成的 Label。Label 在一个 Database 内唯一。当一个 Label 对应的导入作业成功够，不可在重复使用该 Label 提交导入作业。如果 Label 对应的导入作业失败，则可以重复使用。</p>
-<p>用户可以通过 Label 机制，来保证 Label 对应的数据最多被导入一次，级 At-Most-Once 语义。</p>
-</div>
-</div>
-<div class="section" id="id6">
-<h2>同步和异步<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<p>Doris 目前的导入方式分为两类，同步和异步。如果是外部程序接入 Doris 的导入功能，需要判断使用导入方式是哪类再确定接入逻辑。</p>
-<div class="section" id="id7">
-<h3>同步<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h3>
-<p>同步导入方式既用户创建导入任务，Doris 同步执行导入，执行完成后返回用户导入结果。用户可直接根据创建导入任务命令返回的结果同步判断导入是否成功。</p>
-<p>同步类型的导入方式有: <strong>Stream load</strong>，<strong>Insert</strong>。</p>
-<p>操作步骤：</p>
-<ol class="simple">
-<li>用户（外部系统）创建导入任务。</li>
-<li>Doris 返回导入结果。</li>
-<li>用户（外部系统）判断导入结果，如果失败可以再次提交导入任务。</li>
-</ol>
-<p><em>注意：如果用户使用的导入方式是同步返回的，且导入的数据量过大，则创建导入请求可能会花很长时间才能返回结果。</em></p>
-</div>
-<div class="section" id="id8">
-<h3>异步<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
-<p>异步导入方式既用户创建导入任务后，Doris 直接返回创建成功。<strong>创建成功不代表数据已经导入</strong>。导入任务会被异步执行，用户在创建成功后，需要通过轮询的方式发送查看命令查看导入作业的状态。如果创建失败，则可以根据失败信息，判断是否需要再次创建。</p>
-<p>异步类型的导入方式有：<strong>Broker load</strong>，<strong>Multi load</strong>。</p>
-<p>操作步骤：</p>
-<ol class="simple">
-<li>用户（外部系统）创建导入任务。</li>
-<li>Doris 返回导入创建结果。</li>
-<li>用户（外部系统）判断导入创建结果，成功则进入4，失败回到重试创建导入，回到1。</li>
-<li>用户（外部系统）轮询查看导入任务，直到状态变为 FINISHED 或 CANCELLED。</li>
-</ol>
-</div>
-<div class="section" id="id9">
-<h3>注意事项<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h3>
-<p>无论是异步还是同步的导入类型，都不应该在 Doris 返回导入失败或导入创建失败后，无休止的重试。<strong>外部系统在有限次数重试并失败后，保留失败信息，大部分多次重试均失败问题都是使用方法问题或数据本身问题。</strong></p>
-</div>
-</div>
-<div class="section" id="id10">
-<h2>最佳实践<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h2>
-<p>用户在接入 Doris 导入时，一般会采用程序接入的方式，这样可以保证数据被定期的导入到 Doris 中。下面主要说明了程序接入 Doris 的最佳实践。</p>
-<ol class="simple">
-<li>选择合适的导入方式：根据数据源所在位置选择导入方式。例如：如果原始数据存放在 HDFS 上，则使用 Broker load 导入。</li>
-<li>确定导入方式的协议：如果选择了 Broker load 导入方式，则外部系统需要能使用 MySQL 协议定期提交和查看导入作业。</li>
-<li>确定导入方式的类型：导入方式为同步或异步。比如 Broker load 为异步导入方式，则外部系统在提交创建导入后，必须调用查看导入命令，根据查看导入命令的结果来判断导入是否成功。</li>
-<li>制定 Label 生成策略：Label 生成策略需满足，每一批次数据唯一且固定的原则。这样 Doris 就可以保证 At-Most-Once。</li>
-<li>程序自身保证 At-Least-Once：外部系统需要保证自身的 At-Least-Once，这样就可以保证导入流程的 Exactly-Once。</li>
-</ol>
-</div>
-<div class="section" id="id11">
-<h2>通用系统配置<a class="headerlink" href="#id11" title="Permalink to this headline">¶</a></h2>
-<p>下面主要解释了几个所有导入方式均通用的系统级别的配置。</p>
-<div class="section" id="fe">
-<h3>FE 配置<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<p>以下配置属于 FE 的系统配置，可以通过修改 FE 的配置文件 <code class="docutils literal notranslate"><span class="pre">fe.conf</span></code> 来修改配置。</p>
-<ul>
-<li><p class="first">max_load_timeout_second 和 min_load_timeout_second</p>
-<p>这两个配置含义为：最大的导入超时时间，最小的导入超时时间，以秒为单位。默认的最大超时时间为3天, 默认的最小超时时间为1秒。用户自定义的导入超时时间不可超过这个范围。该参数通用于所有的导入方式。</p>
-</li>
-<li><p class="first">desired_max_waiting_jobs</p>
-<p>在等待队列中的导入任务个数最大值，默认为100。当在 FE 中处于 PENDING 状态（也就是等待执行的）导入个数超过该值，新的导入请求则会被拒绝。</p>
-<p>此配置仅对异步执行的导入有效，当异步执行的导入等待个数超过默认值，则后续的创建导入请求会被拒绝。</p>
-</li>
-<li><p class="first">max_running_txn_num_per_db</p>
-<p>这个配置的含义是说，每个 Database 中正在运行的导入最大个数（不区分导入类型，统一计数）。当当前 Database 正在运行的导入个数超过最大值时，后续的导入不会被执行。如果是同步导入作业，则导入会被拒绝。如果是异步导入作业。则作业会在队列中等待。</p>
-</li>
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-</div>
-<div class="section" id="be">
-<h3>BE 配置<a class="headerlink" href="#be" title="Permalink to this headline">¶</a></h3>
-<p>以下配置属于 BE 的系统配置，可以通过修改 BE 的配置文件 <code class="docutils literal notranslate"><span class="pre">be.conf</span></code> 来修改配置。</p>
-<ul>
-<li><p class="first">push_write_mbytes_per_sec</p>
-<p>BE 上单个 Tablet 的写入速度限制。默认是 10，即 10MB/s。通常 BE 对单个 Tablet 的最大写入速度，根据 Schema 以及系统的不同，大约在 10-30MB/s 之间。可以适当调整这个参数来控制导入速度。</p>
-</li>
-<li><p class="first">write_buffer_size</p>
-<p>导入数据在 BE 上会先写入一个 memtable，memtable 达到阈值后才会写回磁盘。默认大小是 100MB。过小的阈值可能导致 BE 上存在大量的小文件。可以适当提高这个阈值减少文件数量。但过大的阈值可能导致 RPC 超时，见下面的配置说明。</p>
-</li>
-<li><p class="first">tablet_writer_rpc_timeout_sec</p>
-<p>导入过程中，发送一个 Batch（1024行）的 RPC 超时时间。默认 600 秒。因为该 RPC 可能涉及多个 memtable 的写盘操作，所以可能会因为写盘导致 RPC 超时，可以适当调整这个超时时间来减少超时错误（如 <code class="docutils literal notranslate"><span class="pre">send</span> <span class="pre">batch</span> <span class="pre">fail</span></code> 错误）。同时，如果调大 <code class="docutils literal notranslate"><span class="pre">write_buffer_size</span></code> 配置，也需要适当调大这个参数。</p>
-</li>
-<li><p class="first">streaming_load_rpc_max_alive_time_sec</p>
-<p>在导入过程中，Doris 会为每一个 Tablet 开启一个 Writer，用于接收数据并写入。这个参数指定了 Writer 的等待超时时间。如果在这个时间内，Writer 没有收到任何数据，则 Writer 会被自动销毁。当系统处理速度较慢时，Writer 可能长时间接收不到下一批数据，导致导入报错：<code class="docutils literal notranslate"><span class="pre">TabletWriter</span> <span class="pre">add</span> <span class="pre">batch</span> <span class="pre">with</span> <span class="pre">unknown</span> <span class="pre">id</span></code>。此时可适当增大这个配置。默认为 600 秒。</p>
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- <div class="section" id="routine-load">
-<h1>Routine Load<a class="headerlink" href="#routine-load" title="Permalink to this headline">¶</a></h1>
-<p>例行导入（Routine Load）功能为用户提供了一种自动从指定数据源进行数据导入的功能。</p>
-<p>本文档主要介绍该功能的实现原理、使用方式以及最佳实践。</p>
-<div class="section" id="id1">
-<h2>名词解释<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>FE：Frontend，Doris 的前端节点。负责元数据管理和请求接入。</li>
-<li>BE：Backend，Doris 的后端节点。负责查询执行和数据存储。</li>
-<li>RoutineLoadJob：用户提交的一个例行导入作业。</li>
-<li>JobScheduler：例行导入作业调度器，用于调度和拆分一个 RoutineLoadJob 为多个 Task。</li>
-<li>Task：RoutineLoadJob 被 JobScheduler 根据规则拆分的子任务。</li>
-<li>TaskScheduler：任务调度器。用于调度 Task 的执行。</li>
-</ul>
-</div>
-<div class="section" id="id2">
-<h2>原理<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="o">+---------+</span>
- <span class="o">|</span> <span class="n">Client</span> <span class="o">|</span>
- <span class="o">+----+----+</span>
- <span class="o">|</span>
-<span class="o">+-----------------------------+</span>
-<span class="o">|</span> <span class="n">FE</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+-----------</span><span class="n">v</span><span class="o">------------+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">Routine</span> <span class="n">Load</span> <span class="n">Job</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+---+--------+--------+--+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+---</span><span class="n">v</span><span class="o">--+</span> <span class="o">+---</span><span class="n">v</span><span class="o">--+</span> <span class="o">+---</span><span class="n">v</span><span class="o">--+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="n">task</span> <span class="o">|</span> <span class="o">|</span> <span class="n">task</span> <span class="o">|</span> <span class="o">|</span> <span class="n">task</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">+--+---+</span> <span class="o">+---+--+</span> <span class="o">+---+--+</span> <span class="o">|</span>
-<span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
-<span class="o">+-----------------------------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="n">v</span> <span class="n">v</span> <span class="n">v</span>
- <span class="o">+---+--+</span> <span class="o">+--+---+</span> <span class="o">++-----+</span>
- <span class="o">|</span> <span class="n">BE</span> <span class="o">|</span> <span class="o">|</span> <span class="n">BE</span> <span class="o">|</span> <span class="o">|</span> <span class="n">BE</span> <span class="o">|</span>
- <span class="o">+------+</span> <span class="o">+------+</span> <span class="o">+------+</span>
-</pre></div>
-</div>
-<p>如上图，Client 向 FE 提交一个例行导入作业。</p>
-<p>FE 通过 JobScheduler 将一个导入作业拆分成若干个 Task。每个 Task 负责导入指定的一部分数据。Task 被 TaskScheduler 分配到指定的 BE 上执行。</p>
-<p>在 BE 上，一个 Task 被视为一个普通的导入任务，通过 Stream Load 的导入机制进行导入。导入完成后，向 FE 汇报。</p>
-<p>FE 中的 JobScheduler 根据汇报结果，继续生成后续新的 Task，或者对失败的 Task 进行重试。</p>
-<p>整个例行导入作业通过不断的产生新的 Task，来完成数据不间断的导入。</p>
-</div>
-<div class="section" id="kafka">
-<h2>Kafka 例行导入<a class="headerlink" href="#kafka" title="Permalink to this headline">¶</a></h2>
-<p>当前我们仅支持从 Kafka 系统进行例行导入。该部分会详细介绍 Kafka 例行导入使用方式和最佳实践。</p>
-<div class="section" id="id3">
-<h3>使用限制<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h3>
-<ol class="simple">
-<li>支持无认证的 Kafka 访问，以及通过 SSL 方式认证的 Kafka 集群。</li>
-<li>支持的消息格式为 csv 文本格式。每一个 message 为一行，且行尾<strong>不包含</strong>换行符。</li>
-<li>仅支持 Kafka 0.10.0.0(含) 以上版本。</li>
-</ol>
-</div>
-<div class="section" id="id4">
-<h3>创建例行导入任务<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h3>
-<p>创建例行导入任务的的详细语法可以连接到 Doris 后，执行 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">CREATE</span> <span class="pre">ROUTINE</span> <span class="pre">LOAD;</span></code> 查看语法帮助。这里主要详细介绍，创建作业时的注意事项。</p>
-<ul>
-<li><p class="first">columns_mapping</p>
-<p><code class="docutils literal notranslate"><span class="pre">columns_mapping</span></code> 主要用于指定表结构和 message 中的列映射关系，以及一些列的转换。如果不指定，Doris 会默认 message 中的列和表结构的列按顺序一一对应。虽然在正常情况下，如果源数据正好一一对应，则不指定也可以进行正常的数据导入。但是我们依然强烈建议用户<strong>显式的指定列映射关系</strong>。这样当表结构发生变化（比如增加一个 nullable 的列），或者源文件发生变化（比如增加了一列）时，导入任务依然可以继续进行。否则，当发生上述变动后，因为列映射关系不再一一对应，导入将报错。</p>
-<p>在 <code class="docutils literal notranslate"><span class="pre">columns_mapping</span></code> 中我们同样可以使用一些内置函数进行列的转换。但需要注意函数参数对应的实际列类型。举例说明：</p>
-<p>假设用户需要导入只包含 <code class="docutils literal notranslate"><span class="pre">k1</span></code> 一列的表，列类型为 <code class="docutils literal notranslate"><span class="pre">int</span></code>。并且需要将源文件中的 null 值转换为 0。该功能可以通过 <code class="docutils literal notranslate"><span class="pre">ifnull</span></code> 函数实现。正确是的使用方式如下：</p>
-<p><code class="docutils literal notranslate"><span class="pre">COLUMNS</span> <span class="pre">(xx,</span> <span class="pre">k1=ifnull(xx,</span> <span class="pre">"3"))</span></code></p>
-<p>注意这里我们使用 <code class="docutils literal notranslate"><span class="pre">"3"</span></code> 而不是 <code class="docutils literal notranslate"><span class="pre">3</span></code>，虽然 <code class="docutils literal notranslate"><span class="pre">k1</span></code> 的类型为 <code class="docutils literal notranslate"><span class="pre">int</span></code>。因为对于导入任务来说，源数据中的列类型都为 <code class="docutils literal notranslate"><span class="pre">varchar</span></code>，所以这里 <code class="docutils literal notra [...]
-<p>再举例，假设用户需要导入只包含 <code class="docutils literal notranslate"><span class="pre">k1</span></code> 一列的表，列类型为 <code class="docutils literal notranslate"><span class="pre">int</span></code>。并且需要将源文件中的对应列进行处理：将负数转换为正数，而将正数乘以 100。这个功能可以通过 <code class="docutils literal notranslate"><span class="pre">case</span> <span class="pre">when</span></code> 函数实现，正确写法应如下：</p>
-<p><code class="docutils literal notranslate"><span class="pre">COLUMNS</span> <span class="pre">(xx,</span> <span class="pre">case</span> <span class="pre">when</span> <span class="pre">xx</span> <span class="pre"><</span> <span class="pre">0</span> <span class="pre">than</span> <span class="pre">cast(-xx</span> <span class="pre">as</span> <span class="pre">varchar)</span> <span class="pre">else</span> <span class="pre">cast((xx</span> <span class="pre">+</span> <span class="pre">'10 [...]
-<p>注意这里我们需要将 <code class="docutils literal notranslate"><span class="pre">case</span> <span class="pre">when</span></code> 中所有的参数都最终转换为 varchar，才能得到期望的结果。</p>
-</li>
-<li><p class="first">where_predicates</p>
-<p><code class="docutils literal notranslate"><span class="pre">where_predicates</span></code> 中的的列的类型，已经是实际的列类型了，所以无需向 <code class="docutils literal notranslate"><span class="pre">columns_mapping</span></code> 那样强制的转换为 varchar 类型。按照实际的列类型书写即可。</p>
-</li>
-<li><p class="first">desired_concurrent_number</p>
-<p><code class="docutils literal notranslate"><span class="pre">desired_concurrent_number</span></code> 用于指定一个例行作业期望的并发度。即一个作业，最多有多少 task 同时在执行。对于 Kafka 导入而言，当前的实际并发度计算如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Min</span><span class="p">(</span><span class="n">partition</span> <span class="n">num</span><span class="p">,</span> <span class="n">desired_concurrent_number</span><span class="p">,</span> <span class="n">alive_backend_num</span><span class="p">,</span> <span class="n">Config</span><span class="o">.</span><span class="n">max_routine_load_task_concurrrent_num</span><span class="p">)</span>
-</pre></div>
-</div>
-<p>其中 <code class="docutils literal notranslate"><span class="pre">Config.max_routine_load_task_concurrrent_num</span></code> 是系统的一个默认的最大并发数限制。这是一个 FE 配置，可以通过改配置调整。默认为 5。</p>
-<p>其中 partition num 指订阅的 Kafka topic 的 partition 数量。<code class="docutils literal notranslate"><span class="pre">alive_backend_num</span></code> 是当前正常的 BE 节点数。</p>
-</li>
-<li><p class="first">max_batch_interval/max_batch_rows/max_batch_size</p>
-<p>这三个参数用于控制单个任务的执行时间。其中任意一个阈值达到，则任务结束。其中 <code class="docutils literal notranslate"><span class="pre">max_batch_rows</span></code> 用于记录从 Kafka 中读取到的数据行数。<code class="docutils literal notranslate"><span class="pre">max_batch_size</span></code> 用于记录从 Kafka 中读取到的数据量，单位是字节。目前一个任务的消费速率大约为 5-10MB/s。</p>
-<p>那么假设一行数据 500B，用户希望每 100MB 或 10 秒为一个 task。100MB 的预期处理时间是 10-20 秒，对应的行数约为 200000 行。则一个合理的配置为：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="s2">"max_batch_interval"</span> <span class="o">=</span> <span class="s2">"10"</span><span class="p">,</span>
-<span class="s2">"max_batch_rows"</span> <span class="o">=</span> <span class="s2">"200000"</span><span class="p">,</span>
-<span class="s2">"max_batch_size"</span> <span class="o">=</span> <span class="s2">"104857600"</span>
-</pre></div>
-</div>
-<p>以上示例中的参数也是这些配置的默认参数。</p>
-</li>
-<li><p class="first">max_error_number</p>
-<p><code class="docutils literal notranslate"><span class="pre">max_error_number</span></code> 用于控制错误率。在错误率过高的时候，作业会自动暂停。因为整个作业是面向数据流的，且由于数据流的无边界性，我们无法像其他导入任务一样，通过一个错误比例来计算错误率。因此这里提供了一种新的计算方式，来计算数据流中的错误比例。</p>
-<p>我们设定了一个采样窗口。窗口的大小为 <code class="docutils literal notranslate"><span class="pre">max_batch_rows</span> <span class="pre">*</span> <span class="pre">10</span></code>。在一个采样窗口内，如果错误行数超过 <code class="docutils literal notranslate"><span class="pre">max_error_number</span></code>，则作业被暂停。如果没有超过，则下一个窗口重新开始计算错误行数。</p>
-<p>我们假设 <code class="docutils literal notranslate"><span class="pre">max_batch_rows</span></code> 为 200000，则窗口大小为 2000000。设 <code class="docutils literal notranslate"><span class="pre">max_error_number</span></code> 为 20000，即用户预期每 2000000 行的错误行为 20000。即错误率为 1%。但是因为不是每批次任务正好消费 200000 行，所以窗口的实际范围是 [2000000, 2200000]，即有 10% 的统计误差。</p>
-<p>错误行不包括通过 where 条件过滤掉的行。但是包括没有对应的 Doris 表中的分区的行。</p>
-</li>
-<li><p class="first">data_source_properties</p>
-<p><code class="docutils literal notranslate"><span class="pre">data_source_properties</span></code> 中可以指定消费具体的 Kakfa partition。如果不指定，则默认消费所订阅的 topic 的所有 partition。</p>
-<p>注意，当显式的指定了 partition，则导入作业不会再动态的检测 Kafka partition 的变化。如果没有指定，则会根据 kafka partition 的变化，动态调整需要消费的 partition。</p>
-</li>
-</ul>
-<div class="section" id="ssl-kafka">
-<h4>访问 SSL 认证的 Kafka 集群<a class="headerlink" href="#ssl-kafka" title="Permalink to this headline">¶</a></h4>
-<p>访问 SSL 认证的 Kafka 集群需要用户提供用于认证 Kafka Broker 公钥的证书文件（ca.pem）。如果 Kafka 集群同时开启了客户端认证，则还需提供客户端的公钥（client.pem）、密钥文件（client.key），以及密钥密码。这里所需的文件需要先通过 <code class="docutils literal notranslate"><span class="pre">CREAE</span> <span class="pre">FILE</span></code> 命令上传到 Doris 中，<strong>并且 catalog 名称为 <code class="docutils literal notranslate"><span class="pre">kafka</span></code></strong>。<code class="docutils literal notranslate"><span class="pre">CREATE</span> <span class="pre">FILE</span></cod [...]
-<ol>
-<li><p class="first">上传文件</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">CREATE</span> <span class="n">FILE</span> <span class="s2">"ca.pem"</span> <span class="n">PROPERTIES</span><span class="p">(</span><span class="s2">"url"</span> <span class="o">=</span> <span class="s2">"https://example_url/kafka-key/ca.pem"</span><span class="p">,</span> <span class="s2">"catalog"</span> <span class="o">=</span> <span class="s2">&q [...]
-<span class="n">CREATE</span> <span class="n">FILE</span> <span class="s2">"client.key"</span> <span class="n">PROPERTIES</span><span class="p">(</span><span class="s2">"url"</span> <span class="o">=</span> <span class="s2">"https://example_urlkafka-key/client.key"</span><span class="p">,</span> <span class="s2">"catalog"</span> <span class="o">=</span> <span class="s2">"kafka"</span><span class="p">);</span>
-<span class="n">CREATE</span> <span class="n">FILE</span> <span class="s2">"client.pem"</span> <span class="n">PROPERTIES</span><span class="p">(</span><span class="s2">"url"</span> <span class="o">=</span> <span class="s2">"https://example_url/kafka-key/client.pem"</span><span class="p">,</span> <span class="s2">"catalog"</span> <span class="o">=</span> <span class="s2">"kafka"</span><span class="p">);</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">创建例行导入作业</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">CREATE</span> <span class="n">ROUTINE</span> <span class="n">LOAD</span> <span class="n">db1</span><span class="o">.</span><span class="n">job1</span> <span class="n">on</span> <span class="n">tbl1</span>
-<span class="n">PROPERTIES</span>
-<span class="p">(</span>
- <span class="s2">"desired_concurrent_number"</span><span class="o">=</span><span class="s2">"1"</span>
-<span class="p">)</span>
-<span class="n">FROM</span> <span class="n">KAFKA</span>
-<span class="p">(</span>
- <span class="s2">"kafka_broker_list"</span><span class="o">=</span> <span class="s2">"broker1:9091,broker2:9091"</span><span class="p">,</span>
- <span class="s2">"kafka_topic"</span> <span class="o">=</span> <span class="s2">"my_topic"</span><span class="p">,</span>
- <span class="s2">"property.security.protocol"</span> <span class="o">=</span> <span class="s2">"ssl"</span><span class="p">,</span>
- <span class="s2">"property.ssl.ca.location"</span> <span class="o">=</span> <span class="s2">"FILE:ca.pem"</span><span class="p">,</span>
- <span class="s2">"property.ssl.certificate.location"</span> <span class="o">=</span> <span class="s2">"FILE:client.pem"</span><span class="p">,</span>
- <span class="s2">"property.ssl.key.location"</span> <span class="o">=</span> <span class="s2">"FILE:client.key"</span><span class="p">,</span>
- <span class="s2">"property.ssl.key.password"</span> <span class="o">=</span> <span class="s2">"abcdefg"</span>
-<span class="p">);</span>
-</pre></div>
-</div>
-</li>
-</ol>
-<blockquote>
-<div><p>Doris 通过 Kafka 的 C++ API <code class="docutils literal notranslate"><span class="pre">librdkafka</span></code> 来访问 Kafka 集群。<code class="docutils literal notranslate"><span class="pre">librdkafka</span></code> 所支持的参数可以参阅</p>
-<p><code class="docutils literal notranslate"><span class="pre">https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md</span></code></p>
-</div></blockquote>
-</div>
-</div>
-<div class="section" id="id5">
-<h3>查看导入作业状态<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<p>查看<strong>作业</strong>状态的具体命令和示例可以通过 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">SHOW</span> <span class="pre">ROUTINE</span> <span class="pre">LOAD;</span></code> 命令查看。</p>
-<p>查看<strong>任务</strong>运行状态的具体命令和示例可以通过 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">SHOW</span> <span class="pre">ROUTINE</span> <span class="pre">LOAD</span> <span class="pre">TASK;</span></code> 命令查看。</p>
-<p>只能查看当前正在运行中的任务，已结束和未开始的任务无法查看。</p>
-</div>
-<div class="section" id="id6">
-<h3>作业控制<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h3>
-<p>用户可以通过 <code class="docutils literal notranslate"><span class="pre">STOP/PAUSE/RESUME</span></code> 三个命令来控制作业的停止，暂停和重启。可以通过 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">STOP</span> <span class="pre">ROUTINE</span> <span class="pre">LOAD;</span></code>, <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">PAUSE</span> <span class="pre">ROUTINE</span> <span class="pre">LOAD;</span></code> 以及 <code class= [...]
-</div>
-</div>
-<div class="section" id="id7">
-<h2>其他说明<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
-<ol>
-<li><p class="first">例行导入作业和 ALTER TABLE 操作的关系</p>
-<ul class="simple">
-<li>例行导入不会阻塞 SCHEMA CHANGE 和 ROLLUP 操作。但是注意如果 SCHEMA CHANGE 完成后，列映射关系无法匹配，则会导致作业的错误数据激增，最终导致作业暂停。建议通过在例行导入作业中显式指定列映射关系，以及通过增加 Nullable 列或带 Default 值的列来减少这类问题。</li>
-<li>删除表的 Partition 可能会导致导入数据无法找到对应的 Partition，作业进入暂停。</li>
-</ul>
-</li>
-<li><p class="first">例行导入作业和其他导入作业的关系（LOAD, DELETE, INSERT）</p>
-<ul class="simple">
-<li>例行导入和其他 LOAD 作业以及 INSERT 操作没有冲突。</li>
-<li>当执行 DELETE 操作时，对应表分区不能有任何正在执行的导入任务。所以在执行 DELETE 操作前，可能需要先暂停例行导入作业，并等待已下发的 task 全部完成后，才可以执行 DELETE。</li>
-</ul>
-</li>
-<li><p class="first">例行导入作业和 DROP DATABASE/TABLE 操作的关系</p>
-<p>当例行导入对应的 database 或 table 被删除后，作业会自动 CANCEL。</p>
-</li>
-<li><p class="first">kafka 类型的例行导入作业和 kafka topic 的关系</p>
-<p>当用户在创建例行导入声明的 <code class="docutils literal notranslate"><span class="pre">kafka_topic</span></code> 在kafka集群中不存在时。</p>
-<ul class="simple">
-<li>如果用户 kafka 集群的 broker 设置了 <code class="docutils literal notranslate"><span class="pre">auto.create.topics.enable</span> <span class="pre">=</span> <span class="pre">true</span></code>，则 <code class="docutils literal notranslate"><span class="pre">kafka_topic</span></code> 会先被自动创建，自动创建的 partition 个数是由<strong>用户方的kafka集群</strong>中的 broker 配置 <code class="docutils literal notranslate"><span class="pre">num.partitions</span></code> 决定的。例行作业会正常的不断读取该 topic 的数据。</li>
-<li>如果用户 kafka 集群的 broker 设置了 <code class="docutils literal notranslate"><span class="pre">auto.create.topics.enable</span> <span class="pre">=</span> <span class="pre">false</span></code>, 则 topic 不会被自动创建，例行作业会在没有读取任何数据之前就被暂停，状态为 <code class="docutils literal notranslate"><span class="pre">PAUSED</span></code>。</li>
-</ul>
-<p>所以，如果用户希望当 kafka topic 不存在的时候，被例行作业自动创建的话，只需要将<strong>用户方的kafka集群</strong>中的 broker 设置 <code class="docutils literal notranslate"><span class="pre">auto.create.topics.enable</span> <span class="pre">=</span> <span class="pre">true</span></code> 即可。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="id8">
-<h2>相关参数<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h2>
-<p>一些系统配置参数会影响例行导入的使用。</p>
-<ol>
-<li><p class="first">max_routine_load_task_concurrent_num</p>
-<p>FE 配置项，默认为 5，可以运行时修改。该参数限制了一个例行导入最大的子任务并发数。建议维持默认值。设置过大，可能导致同时并发的任务数过多，占用集群资源。</p>
-</li>
-<li><p class="first">max_consumer_num_per_group</p>
-<p>BE 配置项，默认为 3。该参数表示一个子任务中最多生成几个 consumer 进行数据消费。对于 Kafka 数据源，一个 consumer 可能消费一个或多个 kafka partition。假设一个任务需要消费 6 个 kafka partition，则会生成 3 个 consumer，每个 consumer 消费 2 个 partition。如果只有 2 个 partition，则只会生成 2 个 consumer，每个 consumer 消费 1 个 partition。</p>
-</li>
-<li><p class="first">push_write_mbytes_per_sec</p>
-<p>BE 配置项。默认为 10，即 10MB/s。该参数为导入通用参数，不限于例行导入作业。该参数限制了导入数据写入磁盘的速度。对于 SSD 等高性能存储设备，可以适当增加这个限速。</p>
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- <div class="section" id="stream-load">
-<h1>Stream load<a class="headerlink" href="#stream-load" title="Permalink to this headline">¶</a></h1>
-<p>Stream load 是一个同步的导入方式，用户通过发送 HTTP 协议发送请求将本地文件或数据流导入到 Doris 中。Stream load 同步执行导入并返回导入结果。用户可直接通过请求的返回体判断本次导入是否成功。</p>
-<p>Stream load 主要适用于导入本地文件，或通过程序导入数据流中的数据。</p>
-<div class="section" id="id1">
-<h2>基本原理<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<p>下图展示了 Stream load 的主要流程，省略了一些导入细节。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="o">^</span> <span class="o">+</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="mi">1</span><span class="n">A</span><span class="o">.</span> <span class="n">User</span> <span class="n">submit</span> <span class="n">load</span> <span class="n">to</span> <span class="n">FE</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">+--</span><span class="n">v</span><span class="o">-----------+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="n">FE</span> <span class="o">|</span>
-<span class="mf">5.</span> <span class="n">Return</span> <span class="n">result</span> <span class="n">to</span> <span class="n">user</span> <span class="o">|</span> <span class="o">+--+-----------+</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">|</span> <span class="mf">2.</span> <span class="n">Redirect</span> <span class="n">to</span> <span class="n">BE</span>
- <span class="o">|</span> <span class="o">|</span>
- <span class="o">|</span> <span class="o">+--</span><span class="n">v</span><span class="o">-----------+</span>
- <span class="o">+---+</span><span class="n">Coordinator</span> <span class="n">BE</span><span class="o">|</span> <span class="mi">1</span><span class="n">B</span><span class="o">.</span> <span class="n">User</span> <span class="n">submit</span> <span class="n">load</span> <span class="n">to</span> <span class="n">BE</span>
- <span class="o">+-+-----+----+-+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">+-----+</span> <span class="o">|</span> <span class="o">+-----+</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span> <span class="mf">3.</span> <span class="n">Distrbute</span> <span class="n">data</span>
- <span class="o">|</span> <span class="o">|</span> <span class="o">|</span>
- <span class="o">+-</span><span class="n">v</span><span class="o">-+</span> <span class="o">+-</span><span class="n">v</span><span class="o">-+</span> <span class="o">+-</span><span class="n">v</span><span class="o">-+</span>
- <span class="o">|</span><span class="n">BE</span> <span class="o">|</span> <span class="o">|</span><span class="n">BE</span> <span class="o">|</span> <span class="o">|</span><span class="n">BE</span> <span class="o">|</span>
- <span class="o">+---+</span> <span class="o">+---+</span> <span class="o">+---+</span>
-</pre></div>
-</div>
-<p>Stream load 中，Doris 会选定一个节点作为 Coordinator 节点。该节点负责接数据并分发数据到其他数据节点。</p>
-<p>用户通过 HTTP 协议提交导入命令。如果提交到 FE，则 FE 会通过 HTTP redirect 指令将请求转发给某一个 BE。用户也可以直接提交导入命令给某一指定 BE。</p>
-<p>导入的最终结果由 Coordinator BE 返回给用户。</p>
-</div>
-<div class="section" id="id2">
-<h2>基本操作<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id3">
-<h3>创建导入<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h3>
-<p>Stream load 通过 HTTP 协议提交和传输数据。这里通过 <code class="docutils literal notranslate"><span class="pre">curl</span></code> 命令展示如何提交导入。</p>
-<p>用户也可以通过其他 HTTP client 进行操作。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>curl --location-trusted -u user:passwd [-H ""...] -T data.file -XPUT http://fe_host:http_port/api/{db}/{table}/_stream_load
-
-Header 中支持如下属性：
-label， column_separator， columns， where， max_filter_ratio， partitions
-格式为: -H "key1:value1"
-</pre></div>
-</div>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">curl</span> <span class="o">--</span><span class="n">location</span><span class="o">-</span><span class="n">trusted</span> <span class="o">-</span><span class="n">u</span> <span class="n">root</span> <span class="o">-</span><span class="n">T</span> <span class="n">date</span> <span class="o">-</span><span class="n">H</span> <span class="s2">"label:123"</span> <span class="n">http [...]
-</pre></div>
-</div>
-<p>创建导入的详细语法帮助执行 <code class="docutils literal notranslate"><span class="pre">HELP</span> <span class="pre">STREAM</span> <span class="pre">LOAD</span></code> 查看, 下面主要介绍创建 Stream load 的部分参数意义。</p>
-<div class="section" id="id4">
-<h4>签名参数<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h4>
-<ul>
-<li><p class="first">user/passwd</p>
-<p>Stream load 由于创建导入的协议使用的是 HTTP 协议，通过 Basic access authentication 进行签名。Doris 系统会根据签名验证用户身份和导入权限。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id5">
-<h4>导入任务参数<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h4>
-<p>Stream load 由于使用的是 HTTP 协议，所以所有导入任务有关的参数均设置在 Header 中。下面主要介绍了 Stream load 导入任务参数的部分参数意义。</p>
-<ul>
-<li><p class="first">label</p>
-<p>导入任务的标识。每个导入任务，都有一个在单 database 内部唯一的 label。label 是用户在导入命令中自定义的名称。通过这个 label，用户可以查看对应导入任务的执行情况。</p>
-<p>label 的另一个作用，是防止用户重复导入相同的数据。<strong>强烈推荐用户同一批次数据使用相同的 label。这样同一批次数据的重复请求只会被接受一次，保证了 At-Most-Once</strong></p>
-<p>当 label 对应的导入作业状态为 CANCELLED 时，该 label 可以再次被使用。</p>
-</li>
-<li><p class="first">max_filter_ratio</p>
-<p>导入任务的最大容忍率，默认为0容忍，取值范围是0~1。当导入的错误率超过该值，则导入失败。</p>
-<p>如果用户希望忽略错误的行，可以通过设置这个参数大于 0，来保证导入可以成功。</p>
-<p>计算公式为：</p>
-<p><code class="docutils literal notranslate"><span class="pre">(dpp.abnorm.ALL</span> <span class="pre">/</span> <span class="pre">(dpp.abnorm.ALL</span> <span class="pre">+</span> <span class="pre">dpp.norm.ALL</span> <span class="pre">)</span> <span class="pre">)</span> <span class="pre">></span> <span class="pre">max_filter_ratio</span></code></p>
-<p><code class="docutils literal notranslate"><span class="pre">dpp.abnorm.ALL</span></code> 表示数据质量不合格的行数。如类型不匹配，列数不匹配，长度不匹配等等。</p>
-<p><code class="docutils literal notranslate"><span class="pre">dpp.norm.ALL</span></code> 指的是导入过程中正确数据的条数。可以通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">LOAD</span></code> 命令查询导入任务的正确数据量。</p>
-<p>原始文件的行数 = <code class="docutils literal notranslate"><span class="pre">dpp.abnorm.ALL</span> <span class="pre">+</span> <span class="pre">dpp.norm.ALL</span></code></p>
-</li>
-<li><p class="first">where</p>
-<p>导入任务指定的过滤条件。Stream load 支持对原始数据指定 where 语句进行过滤。被过滤的数据将不会被导入，也不会参与 filter ratio 的计算，但会被计入<code class="docutils literal notranslate"><span class="pre">num_rows_unselected</span></code>。</p>
-</li>
-<li><p class="first">partition</p>
-<p>待导入表的 Partition 信息，如果待导入数据不属于指定的 Partition 则不会被导入。这些数据将计入 <code class="docutils literal notranslate"><span class="pre">dpp.abnorm.ALL</span> </code></p>
-</li>
-<li><p class="first">columns</p>
-<p>待导入数据的函数变换配置，目前 Stream load 支持的函数变换方法包含列的顺序变化以及表达式变换，其中表达式变换的方法与查询语句的一致。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>列顺序变换例子：原始数据有两列，目前表也有两列（c1,c2）但是原始文件的第一列对应的是目标表的c2列, 而原始文件的第二列对应的是目标表的c1列，则写法如下：
-columns: c2,c1
-
-表达式变换例子：原始文件有两列，目标表也有两列（c1,c2）但是原始文件的两列均需要经过函数变换才能对应目标表的两列，则写法如下：
-columns: tmp_c1, tmp_c2, c1 = year(tmp_c1), c2 = mouth(tmp_c2)
-其中 tmp_*是一个占位符，代表的是原始文件中的两个原始列。
-</pre></div>
-</div>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id6">
-<h3>返回结果<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h3>
-<p>由于 Stream load 是一种同步的导入方式，所以导入的结果会通过创建导入的返回值直接返回给用户。</p>
-<p>示例：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="p">{</span>
- <span class="s2">"TxnId"</span><span class="p">:</span> <span class="mi">1003</span><span class="p">,</span>
- <span class="s2">"Label"</span><span class="p">:</span> <span class="s2">"b6f3bc78-0d2c-45d9-9e4c-faa0a0149bee"</span><span class="p">,</span>
- <span class="s2">"Status"</span><span class="p">:</span> <span class="s2">"Success"</span><span class="p">,</span>
- <span class="s2">"Message"</span><span class="p">:</span> <span class="s2">"OK"</span><span class="p">,</span>
- <span class="s2">"NumberTotalRows"</span><span class="p">:</span> <span class="mi">1000000</span><span class="p">,</span>
- <span class="s2">"NumberLoadedRows"</span><span class="p">:</span> <span class="mi">1000000</span><span class="p">,</span>
- <span class="s2">"NumberFilteredRows"</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
- <span class="s2">"NumberUnselectedRows"</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span>
- <span class="s2">"LoadBytes"</span><span class="p">:</span> <span class="mi">40888898</span><span class="p">,</span>
- <span class="s2">"LoadTimeMs"</span><span class="p">:</span> <span class="mi">2144</span><span class="p">,</span>
- <span class="s2">"ErrorURL"</span><span class="p">:</span> <span class="s2">"http://192.168.1.1:8042/api/_load_error_log?file=__shard_0/error_log_insert_stmt_db18266d4d9b4ee5-abb00ddd64bdf005_db18266d4d9b4ee5_abb00ddd64bdf005"</span>
-<span class="p">}</span>
-</pre></div>
-</div>
-<p>下面主要解释了 Stream load 导入结果参数：</p>
-<ul>
-<li><p class="first">TxnId：导入的事务ID。用户可不感知。</p>
-</li>
-<li><p class="first">Label：导入 Label。由用户指定或系统自动生成。</p>
-</li>
-<li><p class="first">Status：导入完成状态。</p>
-<p>“Success”：表示导入成功。</p>
-<p>“Publish Timeout”：该状态也表示导入已经完成，只是数据可能会延迟可见，无需重试。</p>
-<p>“Label Already Exists”：Label 重复，需更换 Label。</p>
-<p>“Fail”：导入失败。</p>
-</li>
-<li><p class="first">Message：导入错误信息。</p>
-</li>
-<li><p class="first">NumberTotalRows：导入总处理的行数。</p>
-</li>
-<li><p class="first">NumberLoadedRows：成功导入的行数。</p>
-</li>
-<li><p class="first">NumberFilteredRows：数据质量不合格的行数。</p>
-</li>
-<li><p class="first">NumberUnselectedRows：被 where 条件过滤的行数。</p>
-</li>
-<li><p class="first">LoadBytes：导入的字节数。</p>
-</li>
-<li><p class="first">LoadTimeMs：导入完成时间。单位毫秒。</p>
-</li>
-<li><p class="first">ErrorURL：如果有数据质量问题，通过访问这个 URL 查看具体错误行。</p>
-</li>
-</ul>
-<blockquote>
-<div>注意：由于 Stream load 是同步的导入方式，所以并不会在 Doris 系统中记录导入信息，用户无法异步的通过查看导入命令看到 Stream load。使用时需监听创建导入请求的返回值获取导入结果。</div></blockquote>
-</div>
-<div class="section" id="id7">
-<h3>取消导入<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h3>
-<p>用户无法手动取消 Stream load，Stream load 在超时或者导入错误后会被系统自动取消。</p>
-</div>
-</div>
-<div class="section" id="id8">
-<h2>相关系统配置<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>FE 配置<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<ul>
-<li><p class="first">stream_load_default_timeout_second</p>
-<p>导入任务的超时时间(以秒为单位)，导入任务在设定的 timeout 时间内未完成则会被系统取消，变成 CANCELLED。</p>
-<p>目前 Stream load 并不支持自定义导入的 timeout 时间，所有 Stream load 导入的超时时间是统一的，默认的 timeout 时间为300秒。如果导入的源文件无法再规定时间内完成导入，则需要调整 FE 的参数<code class="docutils literal notranslate"><span class="pre">stream_load_default_timeout_second</span></code>。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="be">
-<h3>BE 配置<a class="headerlink" href="#be" title="Permalink to this headline">¶</a></h3>
-<ul>
-<li><p class="first">streaming_load_max_mb</p>
-<p>Stream load 的最大导入大小，默认为 10G，单位是 MB。如果用户的原始文件超过这个值，则需要调整 BE 的参数 <code class="docutils literal notranslate"><span class="pre">streaming_load_max_mb</span></code>。</p>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id9">
-<h2>最佳实践<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id10">
-<h3>应用场景<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h3>
-<p>使用 Stream load 的最合适场景就是原始文件在内存中，或者在磁盘中。其次，由于 Stream load 是一种同步的导入方式，所以用户如果希望用同步方式获取导入结果，也可以使用这种导入。</p>
-</div>
-<div class="section" id="id11">
-<h3>数据量<a class="headerlink" href="#id11" title="Permalink to this headline">¶</a></h3>
-<p>由于 Stream load 的原理是由 BE 发起的导入并分发数据，建议的导入数据量在 1G 到 10G 之间。由于默认的最大 Stream load 导入数据量为 10G，所以如果要导入超过 10G 的文件需要修改 BE 的配置 <code class="docutils literal notranslate"><span class="pre">streaming_load_max_mb</span></code></p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>比如：待导入文件大小为15G
-修改 BE 配置 streaming_load_max_mb 为 16000 即可。
-</pre></div>
-</div>
-<p>Stream load 的默认超时为 300秒，按照 Doris 目前最大的导入限速来看，约超过 3G 的文件就需要修改导入任务默认超时时间了。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>导入任务超时时间 = 导入数据量 / 10M/s （具体的平均导入速度需要用户根据自己的集群情况计算）
-例如：导入一个 10G 的文件
-timeout = 1000s 等于 10G / 10M/s
-</pre></div>
-</div>
-</div>
-<div class="section" id="id12">
-<h3>完整例子<a class="headerlink" href="#id12" title="Permalink to this headline">¶</a></h3>
-<p>数据情况： 数据在发送导入请求端的本地磁盘路径 /home/store_sales 中，导入的数据量约为 15G，希望导入到数据库 bj_sales 的表 store_sales 中。</p>
-<p>集群情况：Stream load 的并发数不受集群大小影响。</p>
-<ul>
-<li><p class="first">step1: 导入文件大小是否超过默认的最大导入大小10G</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">修改</span> <span class="n">BE</span> <span class="n">conf</span>
-<span class="n">streaming_load_max_mb</span> <span class="o">=</span> <span class="mi">16000</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">step2: 计算大概的导入时间是否超过默认 timeout 值</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>导入时间 ≈ 15000 / 10 = 1500s
-超过了默认的 timeout 时间，需要修改 FE 的配置
-stream_load_default_timeout_second = 1500
-</pre></div>
-</div>
-</li>
-<li><p class="first">step3：创建导入任务</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">curl</span> <span class="o">--</span><span class="n">location</span><span class="o">-</span><span class="n">trusted</span> <span class="o">-</span><span class="n">u</span> <span class="n">user</span><span class="p">:</span><span class="n">password</span> <span class="o">-</span><span class="n">T</span> <span class="o">/</span><span class="n">home</span><span class="o">/</span><span class=" [...]
-</pre></div>
-</div>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id13">
-<h2>常见问题<a class="headerlink" href="#id13" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">Label Already Exists</p>
-<p>Stream load 的 Label 重复排查步骤如下：</p>
-<ol>
-<li><p class="first">是否和其他导入方式已经存在的导入 Label 冲突：</p>
-<p>由于 Doris 系统中导入的 Label 不区分导入方式，所以存在其他导入方式使用了相同 Label 的问题。</p>
-<p>通过 <code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">LOAD</span> <span class="pre">WHERE</span> <span class="pre">LABEL</span> <span class="pre">=</span> <span class="pre">“xxx”</span></code>，其中 xxx 为重复的 Label 字符串，查看是否已经存在一个 FINISHED 导入的 Label 和用户申请创建的 Label 相同。</p>
-</li>
-<li><p class="first">是否 Stream load 同一个作业被重复提交了</p>
-<p>由于 Stream load 是 HTTP 协议提交创建导入任务，一般各个语言的 HTTP Client 均会自带请求重试逻辑。Doris 系统在接受到第一个请求后，已经开始操作 Stream load，但是由于没有及时返回给 Client 端结果， Client 端会发生再次重试创建请求的情况。这时候 Doris 系统由于已经在操作第一个请求，所以第二个请求已经就会被报 Label Already Exists 的情况。</p>
-<p>排查上述可能的方法：使用 Label 搜索 FE Master 的日志，看是否存在同一个 Label 出现了两次 <code class="docutils literal notranslate"><span class="pre">redirect</span> <span class="pre">load</span> <span class="pre">action</span> <span class="pre">to</span> <span class="pre">destination=</span> </code> 的情况。如果有就说明，请求被 Client 端重复提交了。</p>
-<p>建议用户根据当前请求的数据量，计算出大致导入的时间，并根据导入超时时间改大 Client 端的请求超时时间，避免请求被 Client 端多次提交。</p>
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diff --git a/content/Docs/cn/administrator-guide/operation/index.html b/content/Docs/cn/administrator-guide/operation/index.html
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diff --git a/content/Docs/cn/administrator-guide/operation/metadata-operation.html b/content/Docs/cn/administrator-guide/operation/metadata-operation.html
deleted file mode 100644
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+++ /dev/null
@@ -1,543 +0,0 @@
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- <div class="section" id="id1">
-<h1>元数据运维<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h1>
-<p>本文档主要介绍在实际生产环境中，如何对 Doris 的元数据进行管理。包括 FE 节点建议的部署方式、一些常用的操作方法、以及常见错误的解决方法。</p>
-<p>在阅读本文当前，请先阅读 <a class="reference internal" href="../../internal/metadata-design.html"><span class="doc">Doris 元数据设计文档</span></a> 了解 Doris 元数据的工作原理。</p>
-<div class="section" id="id2">
-<h2>重要提示<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>当前元数据的设计是无法向后兼容的。即如果新版本有新增的元数据结构变动（可以查看 FE 代码中的 <code class="docutils literal notranslate"><span class="pre">FeMetaVersion.java</span></code> 文件中是否有新增的 VERSION），那么在升级到新版本后，通常是无法在回滚到旧版本的。所以，在升级 FE 之前，请务必按照 <a class="reference internal" href="../../installing/upgrade.html"><span class="doc">升级文档</span></a> 中的操作，测试元数据兼容性。</li>
-</ul>
-</div>
-<div class="section" id="id3">
-<h2>元数据目录结构<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>我们假设在 fe.conf 中指定的 <code class="docutils literal notranslate"><span class="pre">meta_dir</span></code> 的路径为 <code class="docutils literal notranslate"><span class="pre">/path/to/palo-meta</span></code>。那么一个正常运行中的 Doris 集群，元数据的目录结构应该如下：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>/path/to/palo-meta/
- |-- bdb/
- | |-- 00000000.jdb
- | |-- je.config.csv
- | |-- je.info.0
- | |-- je.info.0.lck
- | |-- je.lck
- | `-- je.stat.csv
- `-- image/
- |-- ROLE
- |-- VERSION
- `-- image.xxxx
-</pre></div>
-</div>
-<ol>
-<li><p class="first">bdb 目录</p>
-<p>我们将 <a class="reference external" href="https://www.oracle.com/technetwork/database/berkeleydb/overview/index-093405.html">bdbje</a> 作为一个分布式的 kv 系统，存放元数据的 journal。这个 bdb 目录相当于 bdbje 的 “数据目录”。</p>
-<p>其中 <code class="docutils literal notranslate"><span class="pre">.jdb</span></code> 后缀的是 bdbje 的数据文件。这些数据文件会随着元数据 journal 的不断增多而越来越多。当 Doris 定期做完 image 后，旧的日志就会被删除。所以正常情况下，这些数据文件的总大小从几 MB 到几 GB 不等（取决于使用 Doris 的方式，如导入频率等）。当数据文件的总大小大于 10GB，则可能需要怀疑是否是因为 image 没有成功，或者分发 image 失败导致的历史 journal 一直无法删除。</p>
-<p><code class="docutils literal notranslate"><span class="pre">je.info.0</span></code> 是 bdbje 的运行日志。这个日志中的时间是 UTC+0 时区的。我们可能在后面的某个版本中修复这个问题。通过这个日志，也可以查看一些 bdbje 的运行情况。</p>
-</li>
-<li><p class="first">image 目录</p>
-<p>image 目录用于存放 Doris 定期生成的元数据镜像文件。通常情况下，你会看到有一个 <code class="docutils literal notranslate"><span class="pre">image.xxxxx</span></code> 的镜像文件。其中 <code class="docutils literal notranslate"><span class="pre">xxxxx</span></code> 是一个数字。这个数字表示该镜像包含 <code class="docutils literal notranslate"><span class="pre">xxxxx</span></code> 号之前的所有元数据 journal。而这个文件的生成时间（通过 <code class="docutils literal notranslate"><span class="pre">ls</span> <span class="pre">-al</span></code> 查看即可）通常就是镜像的生成时间。</p>
-<p>你也可能会看到一个 <code class="docutils literal notranslate"><span class="pre">image.ckpt</span></code> 文件。这是一个正在生成的元数据镜像。通过 <code class="docutils literal notranslate"><span class="pre">du</span> <span class="pre">-sh</span></code> 命令应该可以看到这个文件大小在不断变大，说明镜像内容正在写入这个文件。当镜像写完后，会自动重名为一个新的 <code class="docutils literal notranslate"><span class="pre">image.xxxxx</span></code> 并替换旧的 image 文件。</p>
-<p>只有角色为 Master 的 FE 才会主动定期生成 image 文件。每次生成完后，都会推送给其他非 Master 角色的 FE。当确认其他所有 FE 都收到这个 image 后，Master FE 会删除 bdbje 中就的元数据 journal。所以，如果 image 生成失败，或者 image 推送给其他 FE 失败时，都会导致 bdbje 中的数据不断累积。</p>
-<p><code class="docutils literal notranslate"><span class="pre">ROLE</span></code> 文件记录了 FE 的类型（FOLLOWER 或 OBSERVER），是一个文本文件。</p>
-<p><code class="docutils literal notranslate"><span class="pre">VERSION</span></code> 文件记录了这个 Doris 集群的 cluster id，以及用于各个节点之间访问认证的 token，也是一个文本文件。</p>
-<p><code class="docutils literal notranslate"><span class="pre">ROLE</span></code> 文件和 <code class="docutils literal notranslate"><span class="pre">VERSION</span></code> 文件只可能同时存在，或同时不存在（如第一次启动时）。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="id4">
-<h2>基本操作<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="fe">
-<h3>启动单节点 FE<a class="headerlink" href="#fe" title="Permalink to this headline">¶</a></h3>
-<p>单节点 FE 是最基本的一种部署方式。一个完整的 Doris 集群，至少需要一个 FE 节点。当只有一个 FE 节点时，这个节点的类型为 Follower，角色为 Master。</p>
-<ol>
-<li><p class="first">第一次启动</p>
-<ol>
-<li><p class="first">假设在 fe.conf 中指定的 <code class="docutils literal notranslate"><span class="pre">meta_dir</span></code> 的路径为 <code class="docutils literal notranslate"><span class="pre">/path/to/palo-meta</span></code>。</p>
-</li>
-<li><p class="first">确保 <code class="docutils literal notranslate"><span class="pre">/path/to/palo-meta</span></code> 已存在，权限正确，且目录为空。</p>
-</li>
-<li><p class="first">直接通过 <code class="docutils literal notranslate"><span class="pre">sh</span> <span class="pre">bin/start_fe.sh</span></code> 即可启动。</p>
-</li>
-<li><p class="first">启动后，你应该可以在 fe.log 中看到如下日志：</p>
-<ul class="simple">
-<li>Palo FE starting…</li>
-<li>image does not exist: /path/to/palo-meta/image/image.0</li>
-<li>transfer from INIT to UNKNOWN</li>
-<li>transfer from UNKNOWN to MASTER</li>
-<li>the very first time to open bdb, dbname is 1</li>
-<li>start fencing, epoch number is 1</li>
-<li>finish replay in xxx msec</li>
-<li>QE service start</li>
-<li>thrift server started</li>
-</ul>
-<p>以上日志不一定严格按照这个顺序，但基本类似。</p>
-</li>
-<li><p class="first">单节点 FE 的第一次启动通常不会遇到问题。如果你没有看到以上日志，一般来说是没有仔细按照文档步骤操作，请仔细阅读相关 wiki。</p>
-</li>
-</ol>
-</li>
-<li><p class="first">重启</p>
-<ol>
-<li><p class="first">直接使用 <code class="docutils literal notranslate"><span class="pre">sh</span> <span class="pre">bin/start_fe.sh</span></code> 可以重新启动已经停止的 FE 节点。</p>
-</li>
-<li><p class="first">重启后，你应该可以在 fe.log 中看到如下日志：</p>
-<ul class="simple">
-<li>Palo FE starting…</li>
-<li>finished to get cluster id: xxxx, role: FOLLOWER and node name: xxxx</li>
-<li>如果重启前还没有 image 产生，则会看到：<ul>
-<li>image does not exist: /path/to/palo-meta/image/image.0</li>
-</ul>
-</li>
-<li>如果重启前有 image 产生，则会看到：<ul>
-<li>start load image from /path/to/palo-meta/image/image.xxx. is ckpt: false</li>
-<li>finished load image in xxx ms</li>
-</ul>
-</li>
-<li>transfer from INIT to UNKNOWN</li>
-<li>replayed journal id is xxxx, replay to journal id is yyyy</li>
-<li>transfer from UNKNOWN to MASTER</li>
-<li>finish replay in xxx msec</li>
-<li>master finish replay journal, can write now.</li>
-<li>begin to generate new image: image.xxxx</li>
-<li>start save image to /path/to/palo-meta/image/image.ckpt. is ckpt: true</li>
-<li>finished save image /path/to/palo-meta/image/image.ckpt in xxx ms. checksum is xxxx</li>
-<li>push image.xxx to other nodes. totally xx nodes, push successed xx nodes</li>
-<li>QE service start</li>
-<li>thrift server started</li>
-</ul>
-<p>以上日志不一定严格按照这个顺序，但基本类似。</p>
-</li>
-</ol>
-</li>
-<li><p class="first">常见问题</p>
-<p>对于单节点 FE 的部署，启停通常不会遇到什么问题。如果有问题，请先参照相关 wiki，仔细核对你的操作步骤。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="id5">
-<h3>添加 FE<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h3>
-<p>添加 FE 流程在 <a class="reference external" href="https://github.com/apache/incubator-doris/wiki/Doris-Deploy-%26-Upgrade">部署和升级文档</a> 有详细介绍，不再赘述。这里主要说明一些注意事项，以及常见问题。</p>
-<ol>
-<li><p class="first">注意事项</p>
-<ul class="simple">
-<li>在添加新的 FE 之前，一定先确保当前的 Master FE 运行正常（连接是否正常，JVM 是否正常，image 生成是否正常，bdbje 数据目录是否过大等等）</li>
-<li>第一次启动新的 FE，一定确保添加了 <code class="docutils literal notranslate"><span class="pre">-helper</span></code> 参数指向 Master FE。再次启动时可不用添加 <code class="docutils literal notranslate"><span class="pre">-helper</span></code>。（如果指定了 <code class="docutils literal notranslate"><span class="pre">-helper</span></code>，FE 会直接询问 helper 节点自己的角色，如果没有指定，FE会尝试从 <code class="docutils literal notranslate"><span class="pre">palo-meta/image/</span></code> 目录下的 <code class="docutils literal notranslate"><span cla [...]
-<li>第一次启动新的 FE，一定确保这个 FE 的 <code class="docutils literal notranslate"><span class="pre">meta_dir</span></code> 已经创建、权限正确且为空。</li>
-<li>启动新的 FE，和执行 <code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">ADD</span> <span class="pre">FOLLOWER/OBSERVER</span></code> 语句在元数据添加 FE，这两个操作的顺序没有先后要求。如果先启动了新的 FE，而没有执行语句，则新的 FE 日志中会一直滚动 <code class="docutils literal notranslate"><span class="pre">current</span> <span class="pre">node</span> <span class="pre">is</span> <span class="pre">not</span> <span class="pre">added</span> <span class="pre">to</span> <span [...]
-<li>请确保前一个 FE 添加成功后，再添加下一个 FE。</li>
-<li>建议直接连接到 MASTER FE 执行 <code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">ADD</span> <span class="pre">FOLLOWER/OBSERVER</span></code> 语句。</li>
-</ul>
-</li>
-<li><p class="first">常见问题</p>
-<ol>
-<li><p class="first">this node is DETACHED</p>
-<p>当第一次启动一个待添加的 FE 时，如果 Master FE 上的 palo-meta/bdb 中的数据很大，则可能在待添加的 FE 日志中看到 <code class="docutils literal notranslate"><span class="pre">this</span> <span class="pre">node</span> <span class="pre">is</span> <span class="pre">DETACHED.</span></code> 字样。这时，bdbje 正在复制数据，你可以看到待添加的 FE 的 <code class="docutils literal notranslate"><span class="pre">bdb/</span></code> 目录正在变大。这个过程通常会在数分钟不等（取决于 bdbje 中的数据量）。之后，fe.log 中可能会有一些 bdbje 相关的错误堆栈信息。如果最终日志中显示 <code class="docutils literal notranslate"><spa [...]
-</li>
-<li><p class="first">各种原因导致添加失败</p>
-<ul class="simple">
-<li>如果添加的是 OBSERVER，因为 OBSERVER 类型的 FE 不参与元数据的多数写，理论上可以随意启停。因此，对于添加 OBSERVER 失败的情况。可以直接杀死 OBSERVER FE 的进程，清空 OBSERVER 的元数据目录后，重新进行一遍添加流程。</li>
-<li>如果添加的是 FOLLOWER，因为 FOLLOWER 是参与元数据多数写的。所以有可能FOLLOWER 已经加入 bdbje 选举组内。如果这时只有两个 FOLLOWER 节点（包括 MASTER），那么停掉一个 FE，可能导致另一个 FE 也因无法进行多数写而退出。此时，我们应该先通过 <code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">DROP</span> <span class="pre">FOLLOWER</span></code> 命令，从元数据中删除新添加的 FOLLOWER 节点，然后再杀死 FOLLOWER 进程，清空元数据，重新进行一遍添加流程。</li>
-</ul>
-</li>
-</ol>
-</li>
-</ol>
-</div>
-<div class="section" id="id6">
-<h3>删除 FE<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h3>
-<p>通过 <code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">DROP</span> <span class="pre">FOLLOWER/OBSERVER</span></code> 命令即可删除对应类型的 FE。以下有几点注意事项：</p>
-<ul class="simple">
-<li>对于 OBSERVER 类型的 FE，直接 DROP 即可，无风险。</li>
-<li>对于 FOLLOWER 类型的 FE。首先，应保证在有奇数个 FOLLOWER 的情况下（3个或以上），开始删除操作。<ol>
-<li>如果删除非 MASTER 角色的 FE，建议连接到 MASTER FE，执行 DROP 命令，再杀死进程即可。</li>
-<li>如果要删除 MASTER FE，先确认有奇数个 FOLLOWER FE 并且运行正常。然后先杀死 MASTER FE 的进程。这时会有某一个 FE 被选举为 MASTER。在确认剩下的 FE 运行正常后，连接到新的 MASTER FE，执行 DROP 命令删除之前老的 MASTER FE 即可。</li>
-</ol>
-</li>
-</ul>
-</div>
-</div>
-<div class="section" id="id7">
-<h2>高级操作<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
-<div class="section" id="id8">
-<h3>故障恢复<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h3>
-<p>FE 有可能因为某些原因出现无法启动 bdbje、FE 之间无法同步等问题。现象包括无法进行元数据写操作、没有 MASTER 等等。这时，我们需要手动操作来恢复 FE。手动恢复 FE 的大致原理，是先通过当前 <code class="docutils literal notranslate"><span class="pre">meta_dir</span></code> 中的元数据，启动一个新的 MASTER，然后在逐台添加其他 FE。请严格按照如下步骤操作：</p>
-<ol>
-<li><p class="first">首先，停止所有 FE 进程，同时停止一切业务访问。保证在元数据恢复期间，不会因为外部访问导致其他不可预期的问题。</p>
-</li>
-<li><p class="first">确认哪个 FE 节点的元数据是最新：</p>
-<ul class="simple">
-<li>首先，<strong>务必先备份所有 FE 的 <code class="docutils literal notranslate"><span class="pre">meta_dir</span></code> 目录。</strong></li>
-<li>通常情况下，Master FE 的元数据是最新的。可以查看 <code class="docutils literal notranslate"><span class="pre">meta_dir/image</span></code> 目录下，image.xxxx 文件的后缀，数字越大，则表示元数据越新。</li>
-<li>通常，通过比较所有 FOLLOWER FE 的 image 文件，找出最新的元数据即可。</li>
-<li>之后，我们要使用这个拥有最新元数据的 FE 节点，进行恢复。</li>
-<li>如果使用 OBSERVER 节点的元数据进行恢复会比较麻烦，建议尽量选择 FOLLOWER 节点。</li>
-</ul>
-</li>
-<li><p class="first">以下操作都在由第2步中选择出来的 FE 节点上进行。</p>
-<ol class="simple">
-<li>如果该节点是一个 OBSERVER，先将 <code class="docutils literal notranslate"><span class="pre">meta_dir/image/ROLE</span></code> 文件中的 <code class="docutils literal notranslate"><span class="pre">role=OBSERVER</span></code> 改为 <code class="docutils literal notranslate"><span class="pre">role=FOLLOWER</span></code>。（从 OBSERVER 节点恢复会比较麻烦，先按这里的步骤操作，后面会有单独说明）</li>
-<li>在 fe.conf 中添加配置：<code class="docutils literal notranslate"><span class="pre">metadata_failure_recovery=true</span></code>。</li>
-<li>执行 <code class="docutils literal notranslate"><span class="pre">sh</span> <span class="pre">bin/start_fe.sh</span></code> 启动这个 FE。</li>
-<li>如果正常，这个 FE 会以 MASTER 的角色启动，类似于前面 <code class="docutils literal notranslate"><span class="pre">启动单节点</span> <span class="pre">FE</span></code> 一节中的描述。在 fe.log 应该会看到 <code class="docutils literal notranslate"><span class="pre">transfer</span> <span class="pre">from</span> <span class="pre">XXXX</span> <span class="pre">to</span> <span class="pre">MASTER</span></code> 等字样。</li>
-<li>启动完成后，先连接到这个 FE，执行一些查询导入，检查是否能够正常访问。如果不正常，有可能是操作有误，建议仔细阅读以上步骤，用之前备份的元数据再试一次。如果还是不行，问题可能就比较严重了。</li>
-<li>如果成功，通过 <code class="docutils literal notranslate"><span class="pre">show</span> <span class="pre">frontends;</span></code> 命令，应该可以看到之前所添加的所有 FE，并且当前 FE 是 master。</li>
-<li>将 fe.conf 中的 <code class="docutils literal notranslate"><span class="pre">metadata_failure_recovery=true</span></code> 配置项删除，或者设置为 <code class="docutils literal notranslate"><span class="pre">false</span></code>，然后重启这个 FE（<strong>重要</strong>）。</li>
-</ol>
-<blockquote>
-<div><p>如果你是从一个 OBSERVER 节点的元数据进行恢复的，那么完成如上步骤后，通过 <code class="docutils literal notranslate"><span class="pre">show</span> <span class="pre">frontends;</span></code> 语句你会发现，当前这个 FE 的角色为 OBSERVER，但是 <code class="docutils literal notranslate"><span class="pre">IsMaster</span></code> 显示为 <code class="docutils literal notranslate"><span class="pre">true</span></code>。这是因为，这里看到的 “OBSERVER” 是记录在 Doris 的元数据中的，而是否是 master，是记录在 bdbje 的元数据中的。因为我们是从一个 OBSERVER 节点恢复的，所以这里出现了不一致。请按如下步骤修复这个问题（这个问题我们会在 [...]
-</div></blockquote>
-<blockquote>
-<div><ol class="simple">
-<li>先把除了这个 “OBSERVER” 以外的所有 FE 节点 DROP 掉。</li>
-<li>通过 <code class="docutils literal notranslate"><span class="pre">ADD</span> <span class="pre">FOLLOWER</span></code> 命令，添加一个新的 FOLLOWER FE，假设在 hostA 上。</li>
-<li>在 hostA 上启动一个全新的 FE，通过 <code class="docutils literal notranslate"><span class="pre">-helper</span></code> 的方式加入集群。</li>
-<li>启动成功后，通过 <code class="docutils literal notranslate"><span class="pre">show</span> <span class="pre">frontends;</span></code> 语句，你应该能看到两个 FE，一个是之前的 OBSERVER，一个是新添加的 FOLLOWER，并且 OBSERVER 是 master。</li>
-<li>确认这个新的 FOLLOWER 是可以正常工作之后，用这个新的 FOLLOWER 的元数据，重新执行一遍故障恢复操作。</li>
-<li>以上这些步骤的目的，其实就是人为的制造出一个 FOLLOWER 节点的元数据，然后用这个元数据，重新开始故障恢复。这样就避免了从 OBSERVER 恢复元数据所遇到的不一致的问题。</li>
-</ol>
-</div></blockquote>
-<blockquote>
-<div><p><code class="docutils literal notranslate"><span class="pre">metadata_failure_recovery=true</span></code> 的含义是，清空 “bdbje” 的元数据。这样 bdbje 就不会再联系之前的其他 FE 了，而作为一个独立的 FE 启动。这个参数只有在恢复启动时才需要设置为 true。恢复完成后，一定要设置为 false，否则一旦重启，bdbje 的元数据又会被清空，导致其他 FE 无法正常工作。</p>
-</div></blockquote>
-</li>
-<li><p class="first">第3步执行成功后，我们再通过 <code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">DROP</span> <span class="pre">FOLLOWER/OBSERVER</span></code> 命令，将之前的其他的 FE 从元数据删除后，按加入新 FE 的方式，重新把这些 FE 添加一遍。</p>
-</li>
-<li><p class="first">如果以上操作正常，则恢复完毕。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="id9">
-<h3>FE 类型变更<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h3>
-<p>如果你需要将当前已有的 FOLLOWER/OBSERVER 类型的 FE，变更为 OBSERVER/FOLLOWER 类型，请先按照前面所述的方式删除 FE，再添加对应类型的 FE 即可</p>
-</div>
-<div class="section" id="id10">
-<h3>FE 迁移<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h3>
-<p>如果你需要将一个 FE 从当前节点迁移到另一个节点，分以下几种情况。</p>
-<ol>
-<li><p class="first">非 MASTER 节点的 FOLLOWER，或者 OBSERVER 迁移</p>
-<p>直接添加新的 FOLLOWER/OBSERVER 成功后，删除旧的 FOLLOWER/OBSERVER 即可。</p>
-</li>
-<li><p class="first">单节点 MASTER 迁移</p>
-<p>当只有一个 FE 时，参考 <code class="docutils literal notranslate"><span class="pre">故障恢复</span></code> 一节。将 FE 的 palo-meta 目录拷贝到新节点上，按照 <code class="docutils literal notranslate"><span class="pre">故障恢复</span></code> 一节中，步骤3的方式启动新的 MASTER</p>
-</li>
-<li><p class="first">一组 FOLLOWER 从一组节点迁移到另一组新的节点</p>
-<p>在新的节点上部署 FE，通过添加 FOLLOWER 的方式先加入新节点。再逐台 DROP 掉旧节点即可。在逐台 DROP 的过程中，MASTER 会自动选择在新的 FOLLOWER 节点上。</p>
-</li>
-</ol>
-</div>
-<div class="section" id="id11">
-<h3>更换 FE 端口<a class="headerlink" href="#id11" title="Permalink to this headline">¶</a></h3>
-<p>FE 目前有以下几个端口</p>
-<ul class="simple">
-<li>edit_log_port：bdbje 的通信端口</li>
-<li>http_port：http 端口，也用于推送 image</li>
-<li>rpc_port：FE 的 thrift server port</li>
-<li>query_port：Mysql 连接端口</li>
-</ul>
-<ol>
-<li><p class="first">edit_log_port</p>
-<p>如果需要更换这个端口，则需要参照 <code class="docutils literal notranslate"><span class="pre">故障恢复</span></code> 一节中的操作，进行恢复。因为该端口已经被持久化到 bdbje 自己的元数据中（同时也记录在 Doris 自己的元数据中），需要通过设置 <code class="docutils literal notranslate"><span class="pre">metadata_failure_recovery=true</span></code> 来清空 bdbje 的元数据。</p>
-</li>
-<li><p class="first">http_port</p>
-<p>所有 FE 的 http_port 必须保持一致。所以如果要修改这个端口，则所有 FE 都需要修改并重启。修改这个端口，在多 FOLLOWER 部署的情况下会比较复杂（涉及到鸡生蛋蛋生鸡的问题…），所以不建议有这种操作。如果必须，直接按照 <code class="docutils literal notranslate"><span class="pre">故障恢复</span></code> 一节中的操作吧。</p>
-</li>
-<li><p class="first">rpc_port</p>
-<p>修改配置后，直接重启 FE 即可。Master FE 会通过心跳将新的端口告知 BE。只有 Master FE 的这个端口会被使用。但仍然建议所有 FE 的端口保持一致。</p>
-</li>
-<li><p class="first">query_port</p>
-<p>修改配置后，直接重启 FE 即可。这个只影响到 mysql 的连接目标。</p>
-</li>
-</ol>
-</div>
-</div>
-<div class="section" id="id12">
-<h2>最佳实践<a class="headerlink" href="#id12" title="Permalink to this headline">¶</a></h2>
-<p>FE 的部署推荐，在 <a class="reference internal" href="../../installing/install-deploy.html"><span class="doc">安装与部署文档</span></a> 中有介绍，这里再做一些补充。</p>
-<ul class="simple">
-<li><strong>如果你并不十分了解 FE 元数据的运行逻辑，或者没有足够 FE 元数据的运维经验，我们强烈建议在实际使用中，只部署一个 FOLLOWER 类型的 FE 作为 MASTER，其余 FE 都是 OBSERVER，这样可以减少很多复杂的运维问题！</strong> 不用过于担心 MASTER 单点故障导致无法进行元数据写操作。首先，如果你配置合理，FE 作为 java 进程很难挂掉。其次，如果 MASTER 磁盘损坏（概率非常低），我们也可以用 OBSERVER 上的元数据，通过 <code class="docutils literal notranslate"><span class="pre">故障恢复</span></code> 的方式手动恢复。</li>
-<li>FE 进程的 JVM 一定要保证足够的内存。我们<strong>强烈建议</strong> FE 的 JVM 内存至少在 10GB 以上，推荐 32GB 至 64GB。并且部署监控来监控 JVM 的内存使用情况。因为如果FE出现OOM，可能导致元数据写入失败，造成一些<strong>无法恢复</strong>的故障！</li>
-<li>FE 所在节点要有足够的磁盘空间，以防止元数据过大导致磁盘空间不足。同时 FE 日志也会占用十几G 的磁盘空间。</li>
-</ul>
-</div>
-<div class="section" id="id13">
-<h2>其他常见问题<a class="headerlink" href="#id13" title="Permalink to this headline">¶</a></h2>
-<ol>
-<li><p class="first">fe.log 中一直滚动 <code class="docutils literal notranslate"><span class="pre">meta</span> <span class="pre">out</span> <span class="pre">of</span> <span class="pre">date.</span> <span class="pre">current</span> <span class="pre">time:</span> <span class="pre">xxx,</span> <span class="pre">synchronized</span> <span class="pre">time:</span> <span class="pre">xxx,</span> <span class="pre">has</span> <span class="pre">log:</span> <span class="pre">xxx,</span> <span class="pr [...]
-<p>这个通常是因为 FE 无法选举出 Master。比如配置了 3 个 FOLLOWER，但是只启动了一个 FOLLOWER，则这个 FOLLOWER 会出现这个问题。通常，只要把剩余的 FOLLOWER 启动起来就可以了。如果启动起来后，仍然没有解决问题，那么可能需要按照 <code class="docutils literal notranslate"><span class="pre">故障恢复</span></code> 一节中的方式，手动进行恢复。</p>
-</li>
-<li><p class="first"><code class="docutils literal notranslate"><span class="pre">Clock</span> <span class="pre">delta:</span> <span class="pre">xxxx</span> <span class="pre">ms.</span> <span class="pre">between</span> <span class="pre">Feeder:</span> <span class="pre">xxxx</span> <span class="pre">and</span> <span class="pre">this</span> <span class="pre">Replica</span> <span class="pre">exceeds</span> <span class="pre">max</span> <span class="pre">permissible</span> <span class="pre">d [...]
-<p>bdbje 要求各个节点之间的时钟误差不能超过一定阈值。如果超过，节点会异常退出。我们默认设置的阈值为 5000 ms，由 FE 的参数 <code class="docutils literal notranslate"><span class="pre">max_bdbje_clock_delta_ms</span></code> 控制，可以酌情修改。但我们建议使用 ntp 等时钟同步方式保证 Doris 集群各主机的时钟同步。</p>
-</li>
-<li><p class="first"><code class="docutils literal notranslate"><span class="pre">image/</span></code> 目录下的镜像文件很久没有更新</p>
-<p>Master FE 会默认每 50000 条元数据 journal，生成一个镜像文件。在一个频繁使用的集群中，通常每隔半天到几天的时间，就会生成一个新的 image 文件。如果你发现 image 文件已经很久没有更新了（比如超过一个星期），则可以顺序的按照如下方法，查看具体原因：</p>
-<ol class="simple">
-<li>在 Master FE 的 fe.log 中搜索 <code class="docutils literal notranslate"><span class="pre">memory</span> <span class="pre">is</span> <span class="pre">not</span> <span class="pre">enough</span> <span class="pre">to</span> <span class="pre">do</span> <span class="pre">checkpoint.</span> <span class="pre">Committed</span> <span class="pre">memroy</span> <span class="pre">xxxx</span> <span class="pre">Bytes,</span> <span class="pre">used</span> <span class="pre">memory</span> <span class="pr [...]
-<li>在 Master FE 的 fe.log 中搜索 <code class="docutils literal notranslate"><span class="pre">begin</span> <span class="pre">to</span> <span class="pre">generate</span> <span class="pre">new</span> <span class="pre">image:</span> <span class="pre">image.xxxx</span></code>。如果找到，则说明开始生成 image 了。检查这个线程的后续日志，如果出现 <code class="docutils literal notranslate"><span class="pre">checkpoint</span> <span class="pre">finished</span> <span class="pre">save</span> <span class="pre">image.xxxx</span></code> [...]
-</ol>
-</li>
-<li><p class="first"><code class="docutils literal notranslate"><span class="pre">bdb/</span></code> 目录的大小非常大，达到几个G或更多</p>
-<p>如果在排除无法生成新的 image 的错误后，bdb 目录在一段时间内依然很大。则可能是因为 Master FE 推送 image 不成功。可以在 Master FE 的 fe.log 中搜索 <code class="docutils literal notranslate"><span class="pre">push</span> <span class="pre">image.xxxx</span> <span class="pre">to</span> <span class="pre">other</span> <span class="pre">nodes.</span> <span class="pre">totally</span> <span class="pre">xx</span> <span class="pre">nodes,</span> <span class="pre">push</span> <span class="pre">successed</span> <span class="pre">yy</span> <span [...]
-<p>同时，你也可以在 FE 的配置文件中添加配置：<code class="docutils literal notranslate"><span class="pre">edit_log_roll_num=xxxx</span></code>。该参数设定了每多少条元数据 journal，做一次 image。默认是 50000。可以适当改小这个数字，使得 image 更加频繁，从而加速删除旧的 journal。</p>
-</li>
-<li><p class="first">FOLLOWER FE 接连挂掉</p>
-<p>因为 Doris 的元数据采用多数写策略，即一条元数据 journal 必须至少写入多数个 FOLLOWER FE 后（比如 3 个 FOLLOWER，必须写成功 2 个），才算成功。而如果写入失败，FE 进程会主动退出。那么假设有 A、B、C 三个 FOLLOWER，C 先挂掉，然后 B 再挂掉，那么 A 也会跟着挂掉。所以如 <code class="docutils literal notranslate"><span class="pre">最佳实践</span></code> 一节中所述，如果你没有丰富的元数据运维经验，不建议部署多 FOLLOWER。</p>
-</li>
-<li><p class="first">fe.log 中出现 <code class="docutils literal notranslate"><span class="pre">get</span> <span class="pre">exception</span> <span class="pre">when</span> <span class="pre">try</span> <span class="pre">to</span> <span class="pre">close</span> <span class="pre">previously</span> <span class="pre">opened</span> <span class="pre">bdb</span> <span class="pre">database.</span> <span class="pre">ignore</span> <span class="pre">it</span></code></p>
-<p>如果后面有 <code class="docutils literal notranslate"><span class="pre">ignore</span> <span class="pre">it</span></code> 字样，通常无需处理。如果你有兴趣，可以在 <code class="docutils literal notranslate"><span class="pre">BDBEnvironment.java</span></code> 搜索这个错误，查看相关注释说明。</p>
-</li>
-<li><p class="first">从 <code class="docutils literal notranslate"><span class="pre">show</span> <span class="pre">frontends;</span></code> 看，某个 FE 的 <code class="docutils literal notranslate"><span class="pre">Join</span></code> 列为 <code class="docutils literal notranslate"><span class="pre">true</span></code>，但是实际该 FE 不正常</p>
-<p>通过 <code class="docutils literal notranslate"><span class="pre">show</span> <span class="pre">frontends;</span></code> 查看到的 <code class="docutils literal notranslate"><span class="pre">Join</span></code> 信息。该列如果为 <code class="docutils literal notranslate"><span class="pre">true</span></code>，仅表示这个 FE <strong>曾经加入过</strong> 集群。并不能表示当前仍然正常的存在于集群中。如果为 <code class="docutils literal notranslate"><span class="pre">false</span></code>，则表示这个 FE <strong>从未加入过</strong> 集群。</p>
-</li>
-<li><p class="first">关于 FE 的配置 <code class="docutils literal notranslate"><span class="pre">master_sync_policy</span></code>, <code class="docutils literal notranslate"><span class="pre">replica_sync_policy</span></code> 和 <code class="docutils literal notranslate"><span class="pre">txn_rollback_limit</span></code></p>
-<p><code class="docutils literal notranslate"><span class="pre">master_sync_policy</span></code> 用于指定当 Leader FE 写元数据日志时，是否调用 fsync(), <code class="docutils literal notranslate"><span class="pre">replica_sync_policy</span></code> 用于指定当 FE HA 部署时，其他 Follower FE 在同步元数据时，是否调用 fsync()。在早期的 Doris 版本中，这两个参数默认是 <code class="docutils literal notranslate"><span class="pre">WRITE_NO_SYNC</span></code>，即都不调用 fsync()。在最新版本的 Doris 中，默认已修改为 <code class="docutils literal notranslate"><span class="pre"> [...]
-<ol class="simple">
-<li>对于单 Follower FE 部署，<code class="docutils literal notranslate"><span class="pre">master_sync_policy</span></code> 设置为 <code class="docutils literal notranslate"><span class="pre">SYNC</span></code>，防止 FE 系统宕机导致元数据丢失。</li>
-<li>对于多 Follower FE 部署，可以将 <code class="docutils literal notranslate"><span class="pre">master_sync_policy</span></code> 和 <code class="docutils literal notranslate"><span class="pre">replica_sync_policy</span></code> 设为 <code class="docutils literal notranslate"><span class="pre">WRITE_NO_SYNC</span></code>，因为我们认为多个系统同时宕机的概率非常低。</li>
-</ol>
-<p>如果在单 Follower FE 部署中，<code class="docutils literal notranslate"><span class="pre">master_sync_policy</span></code> 设置为 <code class="docutils literal notranslate"><span class="pre">WRITE_NO_SYNC</span></code>，则可能出现 FE 系统宕机导致元数据丢失。这时如果有其他 Observer FE 尝试重启时，可能会报错：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Node</span> <span class="n">xxx</span> <span class="n">must</span> <span class="n">rollback</span> <span class="n">xx</span> <span class="n">total</span> <span class="n">commits</span><span class="p">(</span><span class="n">numPassedDurableCommits</span> <span class="n">of</span> <span class="n">which</span> <span class="n">were</span> <span class="n">durable</span><span class="p">)</span> [...]
-</pre></div>
-</div>
-<p>意思有部分已经持久化的事务需要回滚，但条数超过上限。这里我们的默认上限是 100，可以通过设置 <code class="docutils literal notranslate"><span class="pre">txn_rollback_limit</span></code> 改变。该操作仅用于尝试正常启动 FE，但已丢失的元数据无法恢复。</p>
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- <div class="section" id="id1">
-<h1>监控和报警<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h1>
-<p>本文档主要介绍 Doris 的监控项及如何采集、展示监控项。以及如何配置报警（TODO）</p>
-<p><a class="reference external" href="https://grafana.com/dashboards/9734/revisions">Dashborad 模板点击下载</a></p>
-<blockquote>
-<div>注：0.9.0（不含）之前的版本请使用 revision 1。0.9.x 版本请使用 revision 2。0.10.x 版本请使用 revision 3。</div></blockquote>
-<p>Dashboard 模板会不定期更新。更新模板的方式见最后一小节。</p>
-<p>欢迎提供更优的 dashboard。</p>
-<div class="section" id="id2">
-<h2>组件<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<p>Doris 使用 <a class="reference external" href="https://prometheus.io/">Prometheus</a> 和 <a class="reference external" href="https://grafana.com/">Grafana</a> 进项监控项的采集和展示。</p>
-<p><img alt="../../../../_images/dashboard_overview.png" src="../../../../_images/dashboard_overview.png" /></p>
-<ol>
-<li><p class="first">Prometheus</p>
-<p>Prometheus 是一款开源的系统监控和报警套件。它可以通过 Pull 或 Push 采集被监控系统的监控项，存入自身的时序数据库中。并且通过丰富的多维数据查询语言，满足用户的不同数据展示需求。</p>
-</li>
-<li><p class="first">Grafana</p>
-<p>Grafana 是一款开源的数据分析和展示平台。支持包括 Prometheus 在内的多个主流时序数据库源。通过对应的数据库查询语句，从数据源中获取展现数据。通过灵活可配置的 Dashboard，快速的将这些数据以图表的形式展示给用户。</p>
-</li>
-</ol>
-<blockquote>
-<div>注: 本文档仅提供一种使用 Prometheus 和 Grafana 进行 Doris 监控数据采集和展示的方式。原则上不开发、维护这些组件。更多关于这些组件的详细介绍，请移步对应官方文档进行查阅。</div></blockquote>
-</div>
-<div class="section" id="id3">
-<h2>监控数据<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<p>Doris 的监控数据通过 Frontend 和 Backend 的 http 接口向外暴露。监控数据以 Key-Value 的文本形式对外展现。每个 Key 还可能有不同的 Label 加以区分。当用户搭建好 Doris 后，可以在浏览器，通过以下接口访问到节点的监控数据：</p>
-<ul class="simple">
-<li>Frontend: <code class="docutils literal notranslate"><span class="pre">fe_host:fe_http_port/metrics</span></code></li>
-<li>Backend: <code class="docutils literal notranslate"><span class="pre">be_host:be_web_server_port/metrics</span></code></li>
-<li>Broker: 暂不提供</li>
-</ul>
-<p>用户将看到如下监控项结果（示例为 FE 部分监控项）：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>```
-# HELP jvm_heap_size_bytes jvm heap stat
-# TYPE jvm_heap_size_bytes gauge
-jvm_heap_size_bytes{type="max"} 41661235200
-jvm_heap_size_bytes{type="committed"} 19785285632
-jvm_heap_size_bytes{type="used"} 10113221064
-# HELP jvm_non_heap_size_bytes jvm non heap stat
-# TYPE jvm_non_heap_size_bytes gauge
-jvm_non_heap_size_bytes{type="committed"} 105295872
-jvm_non_heap_size_bytes{type="used"} 103184784
-# HELP jvm_young_size_bytes jvm young mem pool stat
-# TYPE jvm_young_size_bytes gauge
-jvm_young_size_bytes{type="used"} 6505306808
-jvm_young_size_bytes{type="peak_used"} 10308026368
-jvm_young_size_bytes{type="max"} 10308026368
-# HELP jvm_old_size_bytes jvm old mem pool stat
-# TYPE jvm_old_size_bytes gauge
-jvm_old_size_bytes{type="used"} 3522435544
-jvm_old_size_bytes{type="peak_used"} 6561017832
-jvm_old_size_bytes{type="max"} 30064771072
-# HELP jvm_direct_buffer_pool_size_bytes jvm direct buffer pool stat
-# TYPE jvm_direct_buffer_pool_size_bytes gauge
-jvm_direct_buffer_pool_size_bytes{type="count"} 91
-jvm_direct_buffer_pool_size_bytes{type="used"} 226135222
-jvm_direct_buffer_pool_size_bytes{type="capacity"} 226135221
-# HELP jvm_young_gc jvm young gc stat
-# TYPE jvm_young_gc gauge
-jvm_young_gc{type="count"} 2186
-jvm_young_gc{type="time"} 93650
-# HELP jvm_old_gc jvm old gc stat
-# TYPE jvm_old_gc gauge
-jvm_old_gc{type="count"} 21
-jvm_old_gc{type="time"} 58268
-# HELP jvm_thread jvm thread stat
-# TYPE jvm_thread gauge
-jvm_thread{type="count"} 767
-jvm_thread{type="peak_count"} 831
-...
-```
-</pre></div>
-</div>
-<p>这是一个以 <a class="reference external" href="https://prometheus.io/docs/practices/naming/">Promethus 格式</a> 呈现的监控数据。我们以其中一个监控项为例进行说明：</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># HELP jvm_heap_size_bytes jvm heap stat</span>
-<span class="c1"># TYPE jvm_heap_size_bytes gauge</span>
-<span class="n">jvm_heap_size_bytes</span><span class="p">{</span><span class="nb">type</span><span class="o">=</span><span class="s2">"max"</span><span class="p">}</span> <span class="mi">41661235200</span>
-<span class="n">jvm_heap_size_bytes</span><span class="p">{</span><span class="nb">type</span><span class="o">=</span><span class="s2">"committed"</span><span class="p">}</span> <span class="mi">19785285632</span>
-<span class="n">jvm_heap_size_bytes</span><span class="p">{</span><span class="nb">type</span><span class="o">=</span><span class="s2">"used"</span><span class="p">}</span> <span class="mi">10113221064</span>
-</pre></div>
-</div>
-<ol class="simple">
-<li>“#” 开头的行为注释行。其中 HELP 为该监控项的描述说明；TYPE 表示该监控项的数据类型，示例中为 Gauge，即标量数据。还有 Counter、Histogram 等数据类型。具体可见 <a class="reference external" href="https://prometheus.io/docs/practices/instrumentation/#counter-vs.-gauge,-summary-vs.-histogram">Prometheus 官方文档</a> 。</li>
-<li><code class="docutils literal notranslate"><span class="pre">jvm_heap_size_bytes</span></code> 即监控项的名称（Key）；<code class="docutils literal notranslate"><span class="pre">type="max"</span></code> 即为一个名为 <code class="docutils literal notranslate"><span class="pre">type</span></code> 的 Label，值为 <code class="docutils literal notranslate"><span class="pre">max</span></code>。一个监控项可以有多个 Label。</li>
-<li>最后的数字，如 <code class="docutils literal notranslate"><span class="pre">41661235200</span></code>，即为监控数值。</li>
-</ol>
-</div>
-<div class="section" id="id4">
-<h2>监控架构<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<p>整个监控架构如下图所示：</p>
-<p><img alt="../../../../_images/monitor_arch.png" src="../../../../_images/monitor_arch.png" /></p>
-<ol class="simple">
-<li>黄色部分为 Prometheus 相关组件。Prometheus Server 为 Prometheus 的主进程，目前 Prometheus 通过 Pull 的方式访问 Doris 节点的监控接口，然后将时序数据存入时序数据库 TSDB 中（TSDB 包含在 Prometheus 进程中，无需单独部署）。Prometheus 也支持通过搭建 <a class="reference external" href="https://github.com/prometheus/pushgateway">Push Gateway</a> 的方式，允许被监控系统将监控数据通过 Push 的方式推到 Push Gateway, 再由 Prometheus Server 通过 Pull 的方式从 Push Gateway 中获取数据。</li>
-<li><a class="reference external" href="https://github.com/prometheus/alertmanager">Alert Manager</a> 为 Prometheus 报警组件，需单独部署（暂不提供方案，可参照官方文档自行搭建）。通过 Alert Manager，用户可以配置报警策略，接收邮件、短信等报警。</li>
-<li>绿色部分为 Grafana 相关组件。Grafana Server 为 Grafana 的主进程。启动后，用户可以通过 Web 页面对 Grafana 进行配置，包括数据源的设置、用户设置、Dashboard 绘制等。这里也是最终用户查看监控数据的地方。</li>
-</ol>
-</div>
-<div class="section" id="id5">
-<h2>开始搭建<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h2>
-<p>请在完成 Doris 的部署后，开始搭建监控系统。</p>
-<div class="section" id="prometheus">
-<h3>Prometheus<a class="headerlink" href="#prometheus" title="Permalink to this headline">¶</a></h3>
-<ol>
-<li><p class="first">在 <a class="reference external" href="https://prometheus.io/download/">Prometheus 官网</a> 下载最新版本的 Prometheus。这里我们以 2.3.2-linux-amd64 版本为例。</p>
-</li>
-<li><p class="first">在准备运行监控服务的机器上，解压下载后的 tar 文件。</p>
-</li>
-<li><p class="first">打开配置文件 promethues.yml。这里我们提供一个示例配置并加以说明（配置文件为 yml 格式，一定注意统一的缩进和空格）：</p>
-<p>这里我们使用最简单的静态文件的方式进行监控配置。Prometheus 支持多种 <a class="reference external" href="https://prometheus.io/docs/prometheus/latest/configuration/configuration/">服务发现</a> 方式，可以动态的感知节点的加入和删除。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># my global config</span>
-<span class="k">global</span><span class="p">:</span>
- <span class="n">scrape_interval</span><span class="p">:</span> <span class="mi">15</span><span class="n">s</span> <span class="c1"># 全局的采集间隔，默认是 1m，这里设置为 15s</span>
- <span class="n">evaluation_interval</span><span class="p">:</span> <span class="mi">15</span><span class="n">s</span> <span class="c1"># 全局的规则触发间隔，默认是 1m，这里设置 15s</span>
-
-<span class="c1"># Alertmanager configuration</span>
-<span class="n">alerting</span><span class="p">:</span>
- <span class="n">alertmanagers</span><span class="p">:</span>
- <span class="o">-</span> <span class="n">static_configs</span><span class="p">:</span>
- <span class="o">-</span> <span class="n">targets</span><span class="p">:</span>
- <span class="c1"># - alertmanager:9093</span>
-
-<span class="c1"># A scrape configuration containing exactly one endpoint to scrape:</span>
-<span class="c1"># Here it's Prometheus itself.</span>
-<span class="n">scrape_configs</span><span class="p">:</span>
- <span class="c1"># The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.</span>
- <span class="o">-</span> <span class="n">job_name</span><span class="p">:</span> <span class="s1">'PALO_CLUSTER'</span> <span class="c1"># 每一个 Doris 集群，我们称为一个 job。这里可以给 job 取一个名字，作为 Doris 集群在监控系统中的名字。</span>
- <span class="n">metrics_path</span><span class="p">:</span> <span class="s1">'/metrics'</span> <span class="c1"># 这里指定获取监控项的 restful api。配合下面的 targets 中的 host:port，Prometheus 最终会通过 host:port/metrics_path 来采集监控项。</span>
- <span class="n">static_configs</span><span class="p">:</span> <span class="c1"># 这里开始分别配置 FE 和 BE 的目标地址。所有的 FE 和 BE 都分别写入各自的 group 中。</span>
- <span class="o">-</span> <span class="n">targets</span><span class="p">:</span> <span class="p">[</span><span class="s1">'fe_host1:8030'</span><span class="p">,</span> <span class="s1">'fe_host2:8030'</span><span class="p">,</span> <span class="s1">'fe_host3:8030'</span><span class="p">]</span>
- <span class="n">labels</span><span class="p">:</span>
- <span class="n">group</span><span class="p">:</span> <span class="n">fe</span> <span class="c1"># 这里配置了 fe 的 group，该 group 中包含了 3 个 Frontends</span>
-
- <span class="o">-</span> <span class="n">targets</span><span class="p">:</span> <span class="p">[</span><span class="s1">'be_host1:8040'</span><span class="p">,</span> <span class="s1">'be_host2:8040'</span><span class="p">,</span> <span class="s1">'be_host3:8040'</span><span class="p">]</span>
- <span class="n">labels</span><span class="p">:</span>
- <span class="n">group</span><span class="p">:</span> <span class="n">be</span> <span class="c1"># 这里配置了 be 的 group，该 group 中包含了 3 个 Backends</span>
-
- <span class="o">-</span> <span class="n">job_name</span><span class="p">:</span> <span class="s1">'PALO_CLUSTER_2'</span> <span class="c1"># 我们可以在一个 Prometheus 中监控多个 Doris 集群，这里开始另一个 Doris 集群的配置。配置同上，以下略。</span>
- <span class="n">metrics_path</span><span class="p">:</span> <span class="s1">'/metrics'</span>
- <span class="n">static_configs</span><span class="p">:</span>
- <span class="o">-</span> <span class="n">targets</span><span class="p">:</span> <span class="p">[</span><span class="s1">'fe_host1:8030'</span><span class="p">,</span> <span class="s1">'fe_host2:8030'</span><span class="p">,</span> <span class="s1">'fe_host3:8030'</span><span class="p">]</span>
- <span class="n">labels</span><span class="p">:</span>
- <span class="n">group</span><span class="p">:</span> <span class="n">fe</span>
-
- <span class="o">-</span> <span class="n">targets</span><span class="p">:</span> <span class="p">[</span><span class="s1">'be_host1:8040'</span><span class="p">,</span> <span class="s1">'be_host2:8040'</span><span class="p">,</span> <span class="s1">'be_host3:8040'</span><span class="p">]</span>
- <span class="n">labels</span><span class="p">:</span>
- <span class="n">group</span><span class="p">:</span> <span class="n">be</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">启动 Promethues</p>
-<p>通过以下命令启动 Promethues：</p>
-<p><code class="docutils literal notranslate"><span class="pre">nohup</span> <span class="pre">./prometheus</span> <span class="pre">--web.listen-address="0.0.0.0:8181"</span> <span class="pre">&</span></code></p>
-<p>该命令将后台运行 Prometheus，并指定其 web 端口为 8181。启动后，即开始采集数据，并将数据存放在 data 目录中。</p>
-</li>
-<li><p class="first">停止 Promethues</p>
-<p>目前没有发现正式的进程停止方式，直接 kill -9 即可。当然也可以将 Prometheus 设为一种 service，以 service 的方式启停。</p>
-</li>
-<li><p class="first">访问 Prometheus</p>
-<p>Prometheus 可以通过 web 页面进行简单的访问。通过浏览器打开 8181 端口，即可访问 Prometheus 的页面。点击导航栏中，<code class="docutils literal notranslate"><span class="pre">Status</span></code> -> <code class="docutils literal notranslate"><span class="pre">Targets</span></code>，可以看到所有分组 Job 的监控主机节点。正常情况下，所有节点都应为 <code class="docutils literal notranslate"><span class="pre">UP</span></code>，表示数据采集正常。点击某一个 <code class="docutils literal notranslate"><span class="pre">Endpoint</span></code>，即可看到当前的监控数值。如果节点状态不为 UP，可以先访问 Dor [...]
-</li>
-<li><p class="first">至此，一个简单的 Prometheus 已经搭建、配置完毕。更多高级使用方式，请参阅 <a class="reference external" href="https://prometheus.io/docs/introduction/overview/">官方文档</a></p>
-</li>
-</ol>
-</div>
-<div class="section" id="grafana">
-<h3>Grafana<a class="headerlink" href="#grafana" title="Permalink to this headline">¶</a></h3>
-<ol>
-<li><p class="first">在 <a class="reference external" href="https://grafana.com/grafana/download">Grafana 官网</a> 下载最新版本的 Grafana。这里我们以 5.2.1.linux-amd64 版本为例。</p>
-</li>
-<li><p class="first">在准备运行监控服务的机器上，解压下载后的 tar 文件。</p>
-</li>
-<li><p class="first">打开配置文件 conf/defaults.ini。这里我们仅列举需要改动的配置项，其余配置可使用默认。</p>
-<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># Path to where grafana can store temp files, sessions, and the sqlite3 db (if that is used)</span>
-<span class="n">data</span> <span class="o">=</span> <span class="n">data</span>
-
-<span class="c1"># Directory where grafana can store logs</span>
-<span class="n">logs</span> <span class="o">=</span> <span class="n">data</span><span class="o">/</span><span class="n">log</span>
-
-<span class="c1"># Protocol (http, https, socket)</span>
-<span class="n">protocal</span> <span class="o">=</span> <span class="n">http</span>
-
-<span class="c1"># The ip address to bind to, empty will bind to all interfaces</span>
-<span class="n">http_addr</span> <span class="o">=</span>
-
-<span class="c1"># The http port to use</span>
-<span class="n">http_port</span> <span class="o">=</span> <span class="mi">8182</span>
-</pre></div>
-</div>
-</li>
-<li><p class="first">启动 Grafana</p>
-<p>通过以下命令启动 Grafana</p>
-<p><code class="docutils literal notranslate"><span class="pre">nohuo</span> <span class="pre">./bin/grafana-server</span> <span class="pre">&</span></code></p>
-<p>该命令将后台运行 Grafana，访问端口为上面配置的 8182</p>
-</li>
-<li><p class="first">停止 Grafana</p>
-<p>目前没有发现正式的进程停止方式，直接 kill -9 即可。当然也可以将 Grafana 设为一种 service，以 service 的方式启停。</p>
-</li>
-<li><p class="first">访问 Grafana</p>
-<p>通过浏览器，打开 8182 端口，可以开始访问 Grafana 页面。默认用户名密码为 admin。</p>
-</li>
-<li><p class="first">配置 Grafana</p>
-<p>初次登陆，需要根据提示设置数据源（data source）。我们这里的数据源，即上一步配置的 Prometheus。</p>
-<p>数据源配置的 Setting 页面说明如下：</p>
-<ol class="simple">
-<li>Name: 数据源的名称，自定义，比如 doris_monitor_data_source</li>
-<li>Type: 选择 Prometheus</li>
-<li>URL: 填写 Prometheus 的 web 地址，如 http://host:8181</li>
-<li>Access: 这里我们选择 Server 方式，即通过 Grafana 进程所在服务器，访问 Prometheus。</li>
-<li>其余选项默认即可。</li>
-<li>点击最下方 <code class="docutils literal notranslate"><span class="pre">Save</span> <span class="pre">&</span> <span class="pre">Test</span></code>，如果显示 <code class="docutils literal notranslate"><span class="pre">Data</span> <span class="pre">source</span> <span class="pre">is</span> <span class="pre">working</span></code>，即表示数据源可用。</li>
-<li>确认数据源可用后，点击左边导航栏的 + 号，开始添加 Dashboard。这里我们已经准备好了 Doris 的 Dashboard 模板（本文档开头）。下载完成后，点击上方的 <code class="docutils literal notranslate"><span class="pre">New</span> <span class="pre">dashboard</span></code>-><code class="docutils literal notranslate"><span class="pre">Import</span> <span class="pre">dashboard</span></code>-><code class="docutils literal notranslate"><span class="pre">Upload</span> <span class="pre">.json</span> <span class="pre">File</span></code>，将下载的 json 文件导入。</li>
-<li>导入后，可以命名 Dashboard，默认是 <code class="docutils literal notranslate"><span class="pre">Doris</span> <span class="pre">Overview</span></code>。同时，需要选择数据源，这里选择之前创建的 <code class="docutils literal notranslate"><span class="pre">doris_monitor_data_source</span></code></li>
-<li>点击 <code class="docutils literal notranslate"><span class="pre">Import</span></code>，即完成导入。之后，可以看到 Doris 的 Dashboard 展示。</li>
-</ol>
-</li>
-<li><p class="first">至此，一个简单的 Grafana 已经搭建、配置完毕。更多高级使用方式，请参阅 <a class="reference external" href="http://docs.grafana.org/">官方文档</a></p>
-</li>
-</ol>
-</div>
-</div>
-<div class="section" id="dashboard">
-<h2>Dashboard 说明<a class="headerlink" href="#dashboard" title="Permalink to this headline">¶</a></h2>
-<p>这里我们简要介绍 Doris Dashboard。Dashboard 的内容可能会随版本升级，不断变化，本文档不保证是最新的 Dashboard 说明。</p>
-<ol>
-<li><p class="first">顶栏</p>
-<p><img alt="../../../../_images/dashboard_navibar.png" src="../../../../_images/dashboard_navibar.png" /></p>
-<ul class="simple">
-<li>左上角为 Dashboard 名称。</li>
-<li>右上角显示当前监控时间范围，可以下拉选择不同的时间范围，还可以指定定时刷新页面间隔。</li>
-<li>cluster_name: 即 Prometheus 配置文件中的各个 job_name，代表一个 Doris 集群。选择不同的 cluster，下方的图表将展示对应集群的监控信息。</li>
-<li>fe_master: 对应集群的 Master Frontend 节点。</li>
-<li>fe_instance: 对应集群的所有 Frontend 节点。选择不同的 Frontend，下方的图表将展示对应 Frontend 的监控信息。</li>
-<li>be_instance: 对应集群的所有 Backend 节点。选择不同的 Backend，下方的图表将展示对应 Backend 的监控信息。</li>
-<li>interval: 有些图表展示了速率相关的监控项，这里可选择以多大间隔进行采样计算速率（注：15s 间隔可能导致一些图表无法显示）。</li>
-</ul>
-</li>
-<li><p class="first">Row</p>
-<p><img alt="../../../../_images/dashboard_row.png" src="../../../../_images/dashboard_row.png" /></p>
-<p>Grafana 中，Row 的概念，即一组图表的集合。如上图中的 Overview、Cluster Overview 即两个不同的 Row。可以通过点击 Row，对 Row 进行折叠。当前 Dashboard 有如下 Rows（持续更新中）：</p>
-<ol class="simple">
-<li>Overview: 所有 Doris 集群的汇总展示。</li>
-<li>Cluster Overview: 选定集群的汇总展示。</li>
-<li>Query Statistic: 选定集群的查询相关监控。</li>
-<li>FE JVM: 选定 Frontend 的 JVM 监控。</li>
-<li>BE: 选定集群的 Backends 的汇总展示。</li>
-<li>BE Task: 选定集群的 Backends 任务信息的展示。</li>
-</ol>
-</li>
-<li><p class="first">图表</p>
-<p><img alt="../../../../_images/dashboard_panel.png" src="../../../../_images/dashboard_panel.png" /></p>
-<p>一个典型的图标分为以下几部分：</p>
-<ol class="simple">
-<li>鼠标悬停左上角的 i 图标，可以查看该图表的说明。</li>
-<li>点击下方的图例，可以单独查看某一监控项。再次点击，则显示所有。</li>
-<li>在图表中拖拽可以选定时间范围。</li>
-<li>标题的 [] 中显示选定的集群名称。</li>
-<li>一些数值对应左边的Y轴，一些对应右边的，可以通过图例末尾的 <code class="docutils literal notranslate"><span class="pre">-right</span></code> 区分。</li>
-<li>点击图表名称-><code class="docutils literal notranslate"><span class="pre">Edit</span></code>，可以对图表进行编辑。</li>
-</ol>
-</li>
-</ol>
-</div>
-<div class="section" id="id6">
-<h2>Dashboard 更新<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<ol class="simple">
-<li>点击 Grafana 左边栏的 <code class="docutils literal notranslate"><span class="pre">+</span></code>，点击 <code class="docutils literal notranslate"><span class="pre">Dashboard</span></code>。</li>
-<li>点击左上角的 <code class="docutils literal notranslate"><span class="pre">New</span> <span class="pre">dashboard</span></code>，在点击右侧出现的 <code class="docutils literal notranslate"><span class="pre">Import</span> <span class="pre">dashboard</span></code>。</li>
-<li>点击 <code class="docutils literal notranslate"><span class="pre">Upload</span> <span class="pre">.json</span> <span class="pre">File</span></code>，选择最新的模板文件。</li>
-<li>选择数据源</li>
-<li>点击 <code class="docutils literal notranslate"><span class="pre">Import(Overwrite)</span></code>，完成模板更新。</li>
-</ol>
-</div>
-</div>
-
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-<h1>多租户(Experimental)<a class="headerlink" href="#experimental" title="Permalink to this headline">¶</a></h1>
-<p>该功能为实验性质，暂不建议在生产环境使用。</p>
-<div class="section" id="id1">
-<h2>背景<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
-<p>Doris 作为一款 PB 级别的在线报表与多维分析数据库，对外通过开放云提供云端的数据库服务，并且对于每个云上的客户都单独部署了一套物理集群。对内，一套物理集群部署了多个业务，对于隔离性要求比较高的业务单独搭建了集群。针对以上存在几点问题：</p>
-<ul class="simple">
-<li>部署多套物理集群维护代价大（升级、功能上线、bug修复）。</li>
-<li>一个用户的查询或者查询引起的bug经常会影响其他用户。</li>
-<li>实际生产环境单机只能部署一个BE进程。而多个BE可以更好的解决胖节点问题。并且对于join、聚合操作可以提供更高的并发度。</li>
-</ul>
-<p>综合以上三点，Doris需要新的多租户方案，既能做到较好的资源隔离和故障隔离，同时也能减少维护的代价，满足共有云和私有云的需求。</p>
-</div>
-<div class="section" id="id2">
-<h2>设计原则<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>使用简单</li>
-<li>开发代价小</li>
-<li>方便现有集群的迁移</li>
-</ul>
-</div>
-<div class="section" id="id3">
-<h2>名词解释<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>FE: Frontend，即 Doris 中用于元数据管理即查询规划的模块。</li>
-<li>BE: Backend，即 Doris 中用于存储和查询数据的模块。</li>
-<li>Master: FE 的一种角色。一个Doris集群只有一个Master，其他的FE为Observer或者Follower。</li>
-<li>instance：一个 BE 进程及时一个 instance。</li>
-<li>host：单个物理机</li>
-<li>cluster：即一个集群，由多个instance组成。</li>
-<li>租户：一个cluster属于一个租户。cluster和租户之间是一对一关系。</li>
-<li>database：一个用户创建的数据库</li>
-</ul>
-</div>
-<div class="section" id="id4">
-<h2>主要思路<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
-<ul class="simple">
-<li>一个host上部署多个BE的instance，在进程级别做资源隔离。</li>
-<li>多个instance形成一个cluster，一个cluster分配给一个业务独立的的租户。</li>
-<li>FE增加cluster这一级并负责cluster的管理。</li>
-<li>CPU,IO,内存等资源隔离采用cgroup。</li>
-</ul>
-</div>
-<div class="section" id="id5">
-<h2>设计方案<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h2>
-<p>为了能够达到隔离的目的，引入了<strong>虚拟cluster</strong>的概念。</p>
-<ol class="simple">
-<li>cluster表示一个虚拟的集群，由多个BE的instance组成。多个cluster共享FE。</li>
-<li>一个host上可以启动多个instance。cluster创建时，选取任意指定数量的instance，组成一个cluster。</li>
-<li>创建cluster的同时，会创建一个名为superuser的账户，隶属于该cluster。superuser可以对cluster进行管理、创建数据库、分配权限等。</li>
-<li>Doris启动后，汇创建一个默认的cluster：default_cluster。如果用户不希望使用多cluster的功能，则会提供这个默认的cluster，并隐藏多cluster的其他操作细节。</li>
-</ol>
-<p>具体架构如下图：
-<img alt="../../../../_images/multi_tenant_arch.png" src="../../../../_images/multi_tenant_arch.png" /></p>
-</div>
-<div class="section" id="sql">
-<h2>SQL 接口<a class="headerlink" href="#sql" title="Permalink to this headline">¶</a></h2>
-<ul>
-<li><p class="first">登录</p>
-<p>默认集群登录名： user_name@default_cluster 或者 user_name</p>
-<p>自定义集群登录名：user_name@cluster_name</p>
-<p><code class="docutils literal notranslate"><span class="pre">mysqlclient</span> <span class="pre">-h</span> <span class="pre">host</span> <span class="pre">-P</span> <span class="pre">port</span> <span class="pre">-u</span> <span class="pre">user_name@cluster_name</span> <span class="pre">-p</span> <span class="pre">password</span></code></p>
-</li>
-<li><p class="first">添加、删除、下线（decommission）以及取消下线BE</p>
-<p><code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">ADD</span> <span class="pre">BACKEND</span> <span class="pre">"host:port"</span></code>
-<code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">DROP</span> <span class="pre">BACKEND</span> <span class="pre">"host:port"</span></code>
-<code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">SYSTEM</span> <span class="pre">DECOMMISSION</span> <span class="pre">BACKEND</span> <span class="pre">"host:port"</span></code>
-<code class="docutils literal notranslate"><span class="pre">CANCEL</span> <span class="pre">DECOMMISSION</span> <span class="pre">BACKEND</span> <span class="pre">"host:port"</span></code></p>
-<p>强烈建议使用 DECOMMISSION 而不是 DROP 来删除 BACKEND。DECOMMISSION 操作会首先将需要下线节点上的数据拷贝到集群内其他instance上。之后，才会真正下线。</p>
-</li>
-<li><p class="first">创建集群，并指定superuser账户的密码</p>
-<p><code class="docutils literal notranslate"><span class="pre">CREATE</span> <span class="pre">CLUSTER</span> <span class="pre">cluster_name</span> <span class="pre">PROPERTIES</span> <span class="pre">("instance_num"</span> <span class="pre">=</span> <span class="pre">"10")</span> <span class="pre">identified</span> <span class="pre">by</span> <span class="pre">"password"</span></code></p>
-</li>
-<li><p class="first">进入一个集群</p>
-<p><code class="docutils literal notranslate"><span class="pre">ENTER</span> <span class="pre">cluster_name</span></code></p>
-</li>
-<li><p class="first">集群扩容、缩容</p>
-<p><code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">CLUSTER</span> <span class="pre">cluster_name</span> <span class="pre">PROPERTIES</span> <span class="pre">("instance_num"</span> <span class="pre">=</span> <span class="pre">"10")</span></code></p>
-<p>当指定的实例个数多于cluster现有be的个数，则为扩容，如果少于则为缩容。</p>
-</li>
-<li><p class="first">链接、迁移db</p>
-<p><code class="docutils literal notranslate"><span class="pre">LINK</span> <span class="pre">DATABASE</span> <span class="pre">src_cluster_name.db_name</span> <span class="pre">dest_cluster_name.db_name</span></code></p>
-<p>软链一个cluster的db到另外一个cluster的db ，对于需要临时访问其他cluster的db却不需要进行实际数据迁移的用户可以采用这种方式。</p>
-<p><code class="docutils literal notranslate"><span class="pre">MIGRATE</span> <span class="pre">DATABASE</span> <span class="pre">src_cluster_name.db_name</span> <span class="pre">dest_cluster_name.db_name</span></code></p>
-<p>如果需要对db进行跨cluster的迁移，在链接之后，执行migrate对数据进行实际的迁移。</p>
-<p>迁移不影响当前两个db的查询、导入等操作，这是一个异步的操作，可以通过<code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">MIGRATIONS</span></code>查看迁移的进度。</p>
-</li>
-<li><p class="first">删除集群</p>
-<p><code class="docutils literal notranslate"><span class="pre">DROP</span> <span class="pre">CLUSTER</span> <span class="pre">cluster_name</span></code></p>
-<p>删除集群，要求先手动删除的集群内所有database。</p>
-</li>
-<li><p class="first">其他</p>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">CLUSTERS</span></code></p>
-<p>展示系统内已经创建的集群。只有root用户有该权限。</p>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">BACKENDS</span></code></p>
-<p>查看集群内的BE instance。</p>
-<p><code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">MIGRATIONS</span></code></p>
-<p>展示当前正在进行的db迁移任务。执行完db的迁移后可以通过此命令查看迁移的进度。</p>
-</li>
-</ul>
-</div>
-<div class="section" id="id6">
-<h2>详细设计<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
-<ol>
-<li><p class="first">命名空间隔离</p>
-<p>为了引入多租户，需要对系统内的cluster之间的命名空间进行隔离。</p>
-<p>Doris现有的元数据采用的是image + journal 的方式(元数据的设计见相关文档)。Doris会把涉及元数据的操作的记录为一个 journal （操作日志），然后定时的按照<strong>图1</strong>的方式写成image，加载的时候按照写入的顺序读即可。但是这样就带来一个问题已经写入的格式不容易修改，比如记录数据分布的元数据格式为：database+table+tablet+replica 嵌套，如果按照以往的方式要做cluster之间的命名空间隔离，则需要在database上增加一层cluster，内部元数据的层级变为:cluster+database+table+tablet+replica，如<strong>图2</strong>所示。但加一层带来的问题有：</p>
-<ul class="simple">
-<li>增加一层带来的元数据改动，不兼容，需要按照图2的方式cluster＋db＋table＋tablet＋replica层级写,这样就改变了以往的元数据组织方式，老版本的升级会比较麻烦，比较理想的方式是按照图3在现有元数据的格式下顺序写入cluster的元数据。</li>
-<li>代码里所有用到db、user等，都需要加一层cluster，一工作量大改动的地方多，层级深，多数代码都获取db，现有功能几乎都要改一遍，并且需要在db的锁的基础上嵌套一层cluster的锁。</li>
-</ul>
-<p><img alt="../../../../_images/palo_meta.png" src="../../../../_images/palo_meta.png" /></p>
-<p>综上这里采用了一种通过给db、user名加前缀的方式去隔离内部因为cluster之间db、user名字冲突的问题。</p>
-<p>如下，所有的sql输入涉及db名、user名的，都需要根据自己所在的cluster来拼写db、user的全名。</p>
-<p><img alt="../../../../_images/cluster_namaspace.png" src="../../../../_images/cluster_namaspace.png" /></p>
-<p>采用这种方式以上两个问题不再有。元数据的组织方式也比较简单。即采用<strong>图3</strong>每个cluster记录下属于自己cluster的db、user，以及节点即可。</p>
-</li>
-<li><p class="first">BE 节点管理</p>
-<p>每个cluster都有属于自己的一组instance，可以通过<code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">BACKENDS</span></code>查看，为了区分出instance属于哪个cluster以及使用情况，BE引入了多个状态：</p>
-<ul class="simple">
-<li>free：当一个BE节点被加入系统内，此时be不属于任何cluster的时候处于空闲状态</li>
-<li>using：当创建集群、或者扩容被选取到一个cluster内则处于使用中。</li>
-<li>cluster decommission：如果执行缩容量，则正在执行缩容的be处于此状态。结束后，be状态变为free。</li>
-<li>system decommission：be正在下线中。下线完成后，该be将会被永久删除。</li>
-</ul>
-<p>只有root用户可以通过<code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">PROC</span> <span class="pre">"/backends"</span></code>中cluster这一项查看集群内所有be的是否被使用。为空则为空闲，否则为使用中。<code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">BACKENDS</span></code>只能看到所在cluster的节点。以下是be节点状态变化的示意图。</p>
-<p><img alt="../../../../_images/backend_state.png" src="../../../../_images/backend_state.png" /></p>
-</li>
-<li><p class="first">创建集群</p>
-<p>只有root用户可以创建一个cluster，并指定任意数量的BE instance。</p>
-<p>支持在相同机器上选取多个instance。选择instance的大致原则是：尽可能选取不同机器上的be并且使所有机器上使用的be数尽可能均匀。</p>
-<p>对于使用来讲，每一个user、db都属于一个cluster（root除外）。为了创建user、db，首先需要进入一个cluster。在创建cluster的时候系统会默认生成这个cluster的管理员，即superuser账户。superuser具有在所属cluster内创建db、user，以及查看be节点数的权限。所有的非root用户登录必须指定一个cluster，即<code class="docutils literal notranslate"><span class="pre">user_name@cluster_name</span></code>。</p>
-<p>只有root用户可以通过<code class="docutils literal notranslate"><span class="pre">SHOW</span> <span class="pre">CLUSTER</span></code>查看系统内所有的cluster，并且可以通过@不同的集群名来进入不同的cluster。对于除了root之外的用户cluster都是不可见的。</p>
-<p>为了兼容老版本Doris内置了一个名字叫做default_cluster的集群，这个名字在创建集群的时候不能使用。</p>
-<p><img alt="../../../../_images/user_authority.png" src="../../../../_images/user_authority.png" /></p>
-</li>
-<li><p class="first">集群扩容</p>
-<p>集群扩容的流程同创建集群。会优先选取不在集群之外的host上的BE instance。选取的原则同创建集群。</p>
-</li>
-<li><p class="first">集群缩容、CLUSTER DECOMMISSION</p>
-<p>用户可以通过设置 cluster 的 instance num 来进行集群缩容。</p>
-<p>集群的缩容会优先在BE instance 数量最多的 host 上选取 instance 进行下线。</p>
-<p>用户也可以直接使用 <code class="docutils literal notranslate"><span class="pre">ALTER</span> <span class="pre">CLUSTER</span> <span class="pre">DECOMMISSION</span> <span class="pre">BACKEND</span></code> 来指定BE，进行集群缩容。</p>
-</li>
-</ol>
-<p><img alt="../../../../_images/replica_recover.png" src="../../../../_images/replica_recover.png" /></p>
-<ol>
-<li><p class="first">建表</p>
-<p>为了保证高可用，每个分片的副本必需在不同的机器上。所以建表时，选择副本所在be的策略为在每个host上随机选取一个be。然后从这些be中随机选取所需副本数量的be。总体上做到每个机器上分片分布均匀。</p>
-<p>因此，加入需要创建一个3副本的分片，即使cluster包含3个或以上的instance，但是只有2个或以下的host，依然不能创建该分片。</p>
-</li>
-<li><p class="first">负载均衡</p>
-<p>负载均衡的粒度为cluster级别，cluster之间不做负载均衡。但是在计算负载是在host一级进行的，而一个host上可能存在多个不同cluster的BE instance。 cluster内，会通过每个host上所有分片数目、存储使用率计算负载，然后把负载高的机器上的分片往负载低的机器上拷贝（详见负载均衡相关文档）。</p>
-</li>
-<li><p class="first">LINK DATABASE（软链）</p>
-<p>多个集群之间可以通过软链的方式访问彼此的数据。链接的级别为不同cluster的db。</p>
-<p>通过在一个cluster内，添加需要访问的其他cluster的db的信息，来访问其他cluster中的db。</p>
-<p>当查询链接的db时，所使用的计算以及存储资源为源db所在cluster的资源。</p>
-<p>被软链的db不能在源cluster中删除。只有链接的db被删除后，才可以删除源db。而删除链接db，不会删除源db。</p>
-</li>
-<li><p class="first">MIGRATE DATABASE</p>
-<p>db可以在cluster之间进行物理迁移。</p>
-<p>要迁移db，必须先链接db。执行迁移后数据会迁移到链接的db所在的cluster，并且执行迁移后源db被删除，链接断开。</p>
-<p>数据的迁移，复用了负载均衡以及副本恢复中，复制数据的流程（详见负载均衡相关文档）。具体实现上，在执行<code class="docutils literal notranslate"><span class="pre">MIRAGTE</span></code>命令后，Doris会在元数据中，将源db的所有副本所属的cluster，修改为目的cluster。</p>
-<p>Doris会定期检查集群内机器之间是否均衡、副本是否齐全、是否有多余的副本。db的迁移即借用了这个流程，在检查副本齐全的时候同时检查副本所在的be是否属于该cluster，如果不属于，则记入要恢复的副本。并且副本多余要删除的时候会优先删除cluster外的副本，然后再按照现有的策略选择：宕机的be的副本->clone的副本->版本落后的副本->负载高的host上的副本，直到副本没有多余。</p>
-</li>
-</ol>
-<p><img alt="../../../../_images/cluster_link_and_migrate_db.png" src="../../../../_images/cluster_link_and_migrate_db.png" /></p>
-<ol class="simple">
-<li>BE的进程隔离</li>
-</ol>
-<p>为了实现be进程之间实际cpu、io以及内存的隔离，需要依赖于be的部署。部署的时候需要在外围配置cgroup，把要部署的be的进程都写入cgroup。如果要实现io的物理隔离各be配置的数据存放路径需要在不同磁盘上，这里不做过多的介绍。</p>
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