[flink] branch master updated: [FLINK-25065][docs] Update document for "lookup.cache.caching-missing-key" option for jdbc connector (#17918)

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The following commit(s) were added to refs/heads/master by this push:
     new c782735  [FLINK-25065][docs] Update document for "lookup.cache.caching-missing-key" option for jdbc connector (#17918)
c782735 is described below

commit c782735a872b2b25ee49e019eae21e174e6330e2
Author: gaurav726 <y1...@lnmiit.ac.in>
AuthorDate: Mon Nov 29 18:07:41 2021 +0530

    [FLINK-25065][docs] Update document for "lookup.cache.caching-missing-key" option for jdbc connector (#17918)
---
 docs/content.zh/docs/connectors/table/jdbc.md | 9 +++++++++
 docs/content/docs/connectors/table/jdbc.md    | 4 +++-
 2 files changed, 12 insertions(+), 1 deletion(-)

diff --git a/docs/content.zh/docs/connectors/table/jdbc.md b/docs/content.zh/docs/connectors/table/jdbc.md
index 774362b..ff1cbe4 100644
--- a/docs/content.zh/docs/connectors/table/jdbc.md
+++ b/docs/content.zh/docs/connectors/table/jdbc.md
@@ -209,6 +209,13 @@ ON myTopic.key = MyUserTable.id;
       默认情况下，lookup cache 是未开启的。请参阅下面的 <a href="#lookup-cache">Lookup Cache</a> 部分了解更多详情。</td>
     </tr>
     <tr>
+      <td><h5>lookup.cache.caching-missing-key</h5></td>
+      <td>可选</td>
+      <td style="word-wrap: break-word;">true</td>
+      <td>Boolean</td>
+      <td>标记缓存丢失的键，默认为true</td>
+    </tr>
+    <tr>
       <td><h5>lookup.max-retries</h5></td>
       <td>可选</td>
       <td style="word-wrap: break-word;">3</td>
@@ -280,6 +287,8 @@ lookup cache 的主要目的是用于提高时态表关联 JDBC 连接器的性
 当缓存命中最大缓存行 `lookup.cache.max-rows` 或当行超过最大存活时间 `lookup.cache.ttl` 时，缓存中最老的行将被设置为已过期。
 缓存中的记录可能不是最新的，用户可以将 `lookup.cache.ttl` 设置为一个更小的值以获得更好的刷新数据，但这可能会增加发送到数据库的请求数。所以要做好吞吐量和正确性之间的平衡。
 
+默认情况下，flink 会缓存主键的空查询结果，您可以通过将 `lookup.cache.caching-missing-key` 设置为 false 来切换行为。
+
 ### 幂等写入
 
 如果在 DDL 中定义了主键，JDBC sink 将使用 upsert 语义而不是普通的 INSERT 语句。upsert 语义指的是如果底层数据库中存在违反唯一性约束，则原子地添加新行或更新现有行，这种方式确保了幂等性。
diff --git a/docs/content/docs/connectors/table/jdbc.md b/docs/content/docs/connectors/table/jdbc.md
index 75d6aa2..bffca22 100644
--- a/docs/content/docs/connectors/table/jdbc.md
+++ b/docs/content/docs/connectors/table/jdbc.md
@@ -210,7 +210,7 @@ Connector Options
     <tr>
       <td><h5>lookup.cache.caching-missing-key</h5></td>
       <td>optional</td>
-      <td style="word-wrap: break-word;">3</td>
+      <td style="word-wrap: break-word;">true</td>
       <td>Boolean</td>
       <td>Flag to cache missing key, true by default</td>
     </tr>
@@ -286,6 +286,8 @@ When lookup cache is enabled, each process (i.e. TaskManager) will hold a cache.
 The oldest rows in cache will be expired when the cache hit to the max cached rows `lookup.cache.max-rows` or when the row exceeds the max time to live `lookup.cache.ttl`.
 The cached rows might not be the latest, users can tune `lookup.cache.ttl` to a smaller value to have a better fresh data, but this may increase the number of requests send to database. So this is a balance between throughput and correctness.
 
+By default, flink will cache the empty query result for a Primary key, you can toggle the behaviour by setting `lookup.cache.caching-missing-key` to false. 
+
 ### Idempotent Writes
 
 JDBC sink will use upsert semantics rather than plain INSERT statements if primary key is defined in DDL. Upsert semantics refer to atomically adding a new row or updating the existing row if there is a unique constraint violation in the underlying database, which provides idempotence.