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Posted to commits@arrow.apache.org by gi...@apache.org on 2022/02/16 12:59:58 UTC
[arrow-site] branch asf-site updated: Updating built site (build ebee3f03bb1f9eaed1252ba517f43e0e81c2d0bf)
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new e8b0c5e Updating built site (build ebee3f03bb1f9eaed1252ba517f43e0e81c2d0bf)
e8b0c5e is described below
commit e8b0c5e89934e94ec696dd75f2efe3eb89c99a6c
Author: David Li <li...@gmail.com>
AuthorDate: Wed Feb 16 12:59:52 2022 +0000
Updating built site (build ebee3f03bb1f9eaed1252ba517f43e0e81c2d0bf)
---
blog/2022/02/08/7.0.0-release/index.html | 8 +-
.../02/16/introducing-arrow-flight-sql/index.html | 453 +++++++++++++++++++++
blog/index.html | 15 +
docs/c_glib/index.html | 4 +-
feed.xml | 254 +++++++++---
img/20220216-flight-sql-gettables.svg | 1 +
img/20220216-flight-sql-jdbc-odbc.svg | 1 +
img/20220216-flight-sql-prepared.svg | 1 +
img/20220216-flight-sql-query.svg | 1 +
release/0.1.0.html | 4 +-
release/0.10.0.html | 4 +-
release/0.11.0.html | 4 +-
release/0.11.1.html | 4 +-
release/0.12.0.html | 4 +-
release/0.13.0.html | 4 +-
release/0.14.0.html | 4 +-
release/0.14.1.html | 4 +-
release/0.15.0.html | 4 +-
release/0.15.1.html | 4 +-
release/0.16.0.html | 4 +-
release/0.17.0.html | 4 +-
release/0.17.1.html | 4 +-
release/0.2.0.html | 4 +-
release/0.3.0.html | 4 +-
release/0.4.0.html | 4 +-
release/0.4.1.html | 4 +-
release/0.5.0.html | 4 +-
release/0.6.0.html | 4 +-
release/0.7.0.html | 4 +-
release/0.7.1.html | 4 +-
release/0.8.0.html | 4 +-
release/0.9.0.html | 4 +-
release/1.0.0.html | 4 +-
release/1.0.1.html | 4 +-
release/2.0.0.html | 4 +-
release/3.0.0.html | 4 +-
release/4.0.0.html | 4 +-
release/4.0.1.html | 4 +-
release/5.0.0.html | 4 +-
release/6.0.0.html | 4 +-
release/6.0.1.html | 4 +-
release/7.0.0.html | 4 +-
release/index.html | 4 +-
43 files changed, 735 insertions(+), 139 deletions(-)
diff --git a/blog/2022/02/08/7.0.0-release/index.html b/blog/2022/02/08/7.0.0-release/index.html
index 5701b14..6e27e61 100644
--- a/blog/2022/02/08/7.0.0-release/index.html
+++ b/blog/2022/02/08/7.0.0-release/index.html
@@ -14,8 +14,8 @@
<meta property="og:title" content="Apache Arrow 7.0.0 Release" />
<meta name="author" content="pmc" />
<meta property="og:locale" content="en_US" />
-<meta name="description" content="The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and only expose selected highlights of the release. Many other bugfixes and improvements have been made: we refer you to the complete changelog. Community Since the 6 [...]
-<meta property="og:description" content="The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and only expose selected highlights of the release. Many other bugfixes and improvements have been made: we refer you to the complete changelog. Community Sinc [...]
+<meta name="description" content="The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and only expose selected highlights of the release. Many other bugfixes and improvements have been made: we refer you to the complete changelog. Community Since the 6 [...]
+<meta property="og:description" content="The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and only expose selected highlights of the release. Many other bugfixes and improvements have been made: we refer you to the complete changelog. Community Sinc [...]
<link rel="canonical" href="https://arrow.apache.org/blog/2022/02/08/7.0.0-release/" />
<meta property="og:url" content="https://arrow.apache.org/blog/2022/02/08/7.0.0-release/" />
<meta property="og:site_name" content="Apache Arrow" />
@@ -28,7 +28,7 @@
<meta name="twitter:site" content="@ApacheArrow" />
<meta name="twitter:creator" content="@pmc" />
<script type="application/ld+json">
-{"@context":"https://schema.org","@type":"BlogPosting","author":{"@type":"Person","name":"pmc"},"dateModified":"2022-02-08T01:00:00-05:00","datePublished":"2022-02-08T01:00:00-05:00","description":"The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive an [...]
+{"@context":"https://schema.org","@type":"BlogPosting","author":{"@type":"Person","name":"pmc"},"dateModified":"2022-02-08T01:00:00-05:00","datePublished":"2022-02-08T01:00:00-05:00","description":"The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive an [...]
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@@ -267,7 +267,7 @@ Thanks for your contributions and participation in the project!</p>
<p>Documentation has been generally improved; see the <a href="https://arrow.apache.org/cookbook/">Arrow Cookbook</a> for recipes on how to use Flight in Python and R, and a new <a href="https://github.com/apache/arrow/blob/master/cpp/examples/arrow/flight_grpc_example.cc">example</a> on how to use Flight and gRPC services on the same port.</p>
-<p>This release includes Arrow Flight SQL, a protocol for using Arrow Flight to execute queries against and fetch metadata from SQL databases. Support is included for C++ and Java (but <em>not</em> languages that bind to C++, like Python or R). A more detailed blog post is forthcoming. Note that development is ongoing and the specification is currently experimental.</p>
+<p>This release includes Arrow Flight SQL, a protocol for using Arrow Flight to execute queries against and fetch metadata from SQL databases. Support is included for C++ and Java (but <em>not</em> languages that bind to C++, like Python or R). A more detailed blog post is forthcoming (<em>EDIT</em> 2022/02/16: see the <a href="/blog/2022/02/16/introducing-arrow-flight-sql/">Flight SQL announcement</a>). Note that development is ongoing and the specification is currently experimental.</p>
<h2 id="c-notes">C++ notes</h2>
diff --git a/blog/2022/02/16/introducing-arrow-flight-sql/index.html b/blog/2022/02/16/introducing-arrow-flight-sql/index.html
new file mode 100644
index 0000000..a7190ab
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+++ b/blog/2022/02/16/introducing-arrow-flight-sql/index.html
@@ -0,0 +1,453 @@
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+
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+<meta property="og:title" content="Introducing Apache Arrow Flight SQL: Accelerating Database Access" />
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+<meta property="og:locale" content="en_US" />
+<meta name="description" content="This post introduces Arrow Flight SQL, a protocol for interacting with SQL databases over Arrow Flight. We have been working on this protocol over the last six months, and are looking for feedback, interested contributors, and early adopters." />
+<meta property="og:description" content="This post introduces Arrow Flight SQL, a protocol for interacting with SQL databases over Arrow Flight. We have been working on this protocol over the last six months, and are looking for feedback, interested contributors, and early adopters." />
+<link rel="canonical" href="https://arrow.apache.org/blog/2022/02/16/introducing-arrow-flight-sql/" />
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+<meta property="twitter:title" content="Introducing Apache Arrow Flight SQL: Accelerating Database Access" />
+<meta name="twitter:site" content="@ApacheArrow" />
+<meta name="twitter:creator" content="@José Almeida, James Duong, Vinicius Fraga, Juscelino Junior, David Li, Kyle Porter, Rafael Telles" />
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+<h1>
+ Introducing Apache Arrow Flight SQL: Accelerating Database Access
+</h1>
+<hr class="mt-4 mb-3">
+
+
+
+<p class="mb-4 pb-1">
+ <span class="badge badge-secondary">Published</span>
+ <span class="published mr-3">
+ 16 Feb 2022
+ </span>
+ <br />
+ <span class="badge badge-secondary">By</span>
+
+ José Almeida, James Duong, Vinicius Fraga, Juscelino Junior, David Li, Kyle Porter, Rafael Telles
+
+
+
+</p>
+
+
+ <!--
+
+-->
+
+<p>We would like to introduce Flight SQL, a new client-server protocol developed by the Apache Arrow community for interacting with SQL databases that makes use of the Arrow in-memory columnar format and the Flight RPC framework.</p>
+
+<p>Flight SQL aims to provide broadly similar functionality to existing APIs like JDBC and ODBC, including executing queries; creating prepared statements; and fetching metadata about the supported SQL dialect, available types, defined tables, and so on.
+By building on Apache Arrow, however, Flight SQL makes it easy for clients to talk to Arrow-native databases without converting data.
+And by using <a href="/blog/2019/10/13/introducing-arrow-flight/">Flight</a>, it provides an efficient implementation of a wire format that supports features like encryption and authentication out of the box, while allowing for further optimizations like parallel data access.</p>
+
+<p>While it can be directly used for database access, it is not a direct replacement for JDBC/ODBC. Instead, Flight SQL serves as a concrete wire protocol/driver implementation that can support a JDBC/ODBC driver and reduces implementation burden on databases.</p>
+
+<!-- mermaidjs:
+
+graph LR
+ JDBC[JDBC]
+ ODBC
+ FlightSQL[Flight SQL<br>libraries]
+ ANA[Arrow-native app]
+ DB[(Database with<br>Flight SQL endpoint)]
+
+ JDBC --> FlightSQL
+ ODBC --> FlightSQL
+ ANA --> FlightSQL
+
+ FlightSQL -->|Flight RPC| DB
+
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-jdbc-odbc.svg" alt="Illustration of where Flight SQL sits in the stack. JDBC and ODBC drivers can wrap Flight SQL, or an Arrow-native application can directly use the Flight SQL libraries. Flight SQL in turn talks over Arrow Flight to a database exposing a Flight SQL endpoint." width="90%" class="img-responsive" />
+</div>
+
+<h2 id="motivation">Motivation</h2>
+
+<p>While standards like <a href="https://docs.oracle.com/javase/8/docs/technotes/guides/jdbc/">JDBC</a> and <a href="https://docs.microsoft.com/en-us/sql/odbc/reference/odbc-overview?view=sql-server-ver15">ODBC</a> have served users well for decades, they fall short for databases and clients which wish to use Apache Arrow or columnar data in general.
+Row-based APIs like JDBC or <a href="https://www.python.org/dev/peps/pep-0249/">PEP 249</a> require transposing data in this case, and for a database which is itself columnar, this means that data has to be transposed twice—once to present it in rows for the API, and once to get it back into columns for the consumer.
+Meanwhile, while APIs like ODBC do provide bulk access to result buffers, this data must still be copied into Arrow arrays for use with the broader Arrow ecosystem, as implemented by projects like <a href="https://turbodbc.readthedocs.io/en/latest/">Turbodbc</a>.
+Flight SQL aims to get rid of these intermediate steps.</p>
+
+<p>Flight SQL means database servers can implement a standard interface that is designed around Apache Arrow and columnar data from the start.
+Just like how Arrow provides a standard in-memory format, Flight SQL saves developers from having to design and implement an entirely new wire protocol.
+As mentioned, Flight already implements features like encryption on the wire and authentication of requests, which databases do not need to re-implement.</p>
+
+<p>For clients, Flight SQL provides bulk access to query results without having to convert data from another API or format.
+Additionally, by pushing the work of implementing the wire protocol into the Flight and Flight SQL libraries, less code has to be written for each client language or driver.
+And by using Flight underneath, clients and servers can cooperate to implement optimizations like parallel data access, <a href="/blog/2019/10/13/introducing-arrow-flight/#horizontal-scalability-parallel-and-partitioned-data-access">one of the original goals of Flight itself</a>.
+Databases can return multiple “endpoints” to a Flight SQL client, which can then pull data from all of them in parallel, enabling the database backend to horizontally scale.</p>
+
+<h2 id="flight-sql-basics">Flight SQL Basics</h2>
+
+<p>Flight SQL makes full use of the Flight RPC framework and its extensibility, defining additional request/response messages via <a href="https://developers.google.com/protocol-buffers/">Protobuf</a>.
+We’ll go over the Flight SQL protocol briefly, but C++ and Java already implement clients that manage much of this work.
+The full <a href="https://github.com/apache/arrow/blob/release-7.0.0/format/FlightSql.proto">protocol</a> can be found on GitHub.</p>
+
+<p>Most requests follow this pattern:</p>
+<ol>
+ <li>The client constructs a request using one of the defined Protobuf messages.</li>
+ <li>The client sends the request via the GetSchema RPC method (to get the schema of the response) or the GetFlightInfo RPC method (to execute the request).</li>
+ <li>The client makes request(s) to the endpoints returned from GetFlightInfo to get the response.</li>
+</ol>
+
+<p>Flight SQL defines methods to query database metadata, execute queries, or manipulate prepared statements.</p>
+
+<p>Metadata requests:</p>
+<ul>
+ <li>CommandGetCatalogs: list catalogs in a database.</li>
+ <li>CommandGetCrossReference: list foreign key columns that reference a particular other table.</li>
+ <li>CommandGetDbSchemas: list schemas in a catalog.</li>
+ <li>CommandGetExportedKeys: list foreign keys referencing a table.</li>
+ <li>CommandGetImportedKeys: list foreign keys of a table.</li>
+ <li>CommandGetPrimaryKeys: list primary keys of a table.</li>
+ <li>CommandGetSqlInfo: get information about the database itself and its supported SQL dialect.</li>
+ <li>CommandGetTables: list tables in a catalog/schema.</li>
+ <li>CommandGetTableTypes: list table types supported (e.g. table, view, system table).</li>
+</ul>
+
+<p>Queries:</p>
+<ul>
+ <li>CommandStatementQuery: execute a one-off SQL query.</li>
+ <li>CommandStatementUpdate: execute a one-off SQL update query.</li>
+</ul>
+
+<p>Prepared statements:</p>
+<ul>
+ <li>ActionClosePreparedStatementRequest: close a prepared statement.</li>
+ <li>ActionCreatePreparedStatementRequest: create a new prepared statement.</li>
+ <li>CommandPreparedStatementQuery: execute a prepared statement.</li>
+ <li>CommandPreparedStatementUpdate: execute a prepared statement that updates data.</li>
+</ul>
+
+<p>For example, to list all tables:</p>
+
+<!-- mermaidjs:
+
+sequenceDiagram
+ Client->>Server: GetFlightInfo(CommandGetTables)
+ Server->>Client: FlightInfo{..., Ticket, ...}
+ Client->>Server: DoGet(Ticket)
+ Server->>Client: list of tables as Arrow data
+
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-gettables.svg" alt="Sequence diagram showing how to use CommandGetTables. First, the client calls the GetFlightInfo RPC method with a serialized CommandGetTables message as the argument. The server returns a FlightInfo message containing a Ticket message. The client then calls the DoGet RPC method with the Ticket as the argument, and gets back a stream of Arrow record batches containing the tables in the database." height="363" class="img-responsive" />
+</div>
+
+<p>To execute a query:</p>
+
+<!-- mermaidjs:
+
+sequenceDiagram
+ Client->>Server: GetFlightInfo(CommandStatementQuery)
+ Server->>Client: FlightInfo{..., Ticket, ...}
+ Client->>Server: DoGet(Ticket)
+ Server->>Client: query results as Arrow data
+
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-query.svg" alt="Sequence diagram showing how to use CommandStatementQuery. First, the client calls the GetFlightInfo RPC method with a serialized CommandStatementQuery message as the argument. This message contains the SQL query. The server returns a FlightInfo message containing a Ticket message. The client then calls the DoGet RPC method with the Ticket as the argument, and gets back a stream of Arrow record batches containing the query results." heig [...]
+</div>
+
+<p>To create and execute a prepared statement to insert rows:</p>
+
+<!-- mermaidjs:
+
+sequenceDiagram
+ Client->>Server: DoAction(ActionCreatePreparedStatementRequest)
+ Server->>Client: ActionCreatePreparedStatementResult
+ Client->>Server: DoPut(CommandPreparedStatementUpdate)
+ Client-->>Server: Arrow data representing parameter values
+ Server->>Client: DoPutUpdateResult
+ Client->>Server: DoAction(ActionClosePreparedStatementRequest)
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-prepared.svg" alt="Sequence diagram showing how to use ActionCreatePreparedStatementResult. First, the client calls the DoAction RPC method with a serialized ActionCreatePreparedStatementResult message as the argument. This message contains the SQL query. The server returns a serialized ActionCreatePreparedStatementResult message containing an opaque handle for the prepared statement. The client then calls the DoPut RPC method with a CommandPreparedStat [...]
+</div>
+
+<h2 id="getting-started">Getting Started</h2>
+
+<p>Note that while Flight SQL is shipping as part of Apache Arrow 7.0.0, it is still under development, and detailed documentation is forthcoming.
+However, implementations are already available in C++ and Java, which provide a low-level client that can be used as well as a server skeleton that can be implemented.</p>
+
+<p>For those interested, a <a href="https://github.com/apache/arrow/blob/release-7.0.0/java/flight/flight-sql/src/test/java/org/apache/arrow/flight/sql/example/FlightSqlExample.java">server implementation wrapping Apache Derby</a> and <a href="https://github.com/apache/arrow/blob/release-7.0.0/cpp/src/arrow/flight/sql/example/sqlite_server.h">one wrapping SQLite</a> are available in the source.
+A <a href="https://github.com/apache/arrow/blob/release-7.0.0/cpp/src/arrow/flight/sql/test_app_cli.cc">simple CLI demonstrating the client</a> is also available. Finally, we can look at a brief example of executing a query and fetching results:</p>
+
+<div class="language-cpp highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">flight</span><span class="o">::</span><span class="n">FlightCallOptions</span> <span class="n">call_options</span><span class="p">;</span>
+
+<span class="c1">// Execute the query, getting a FlightInfo describing how to fetch the results</span>
+<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Executing query: '"</span> <span class="o"><<</span> <span class="n">FLAGS_query</span> <span class="o"><<</span> <span class="s">"'"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
+<span class="n">ARROW_ASSIGN_OR_RAISE</span><span class="p">(</span><span class="n">std</span><span class="o">::</span><span class="n">unique_ptr</span><span class="o"><</span><span class="n">flight</span><span class="o">::</span><span class="n">FlightInfo</span><span class="o">></span> <span class="n">flight_info</span><span class="p">,</span>
+ <span class="n">client</span><span class="o">-></span><span class="n">Execute</span><span class="p">(</span><span class="n">call_options</span><span class="p">,</span> <span class="n">FLAGS_query</span><span class="p">));</span>
+
+<span class="c1">// Fetch each partition sequentially (though this can be done in parallel)</span>
+<span class="k">for</span> <span class="p">(</span><span class="k">const</span> <span class="n">flight</span><span class="o">::</span><span class="n">FlightEndpoint</span><span class="o">&</span> <span class="n">endpoint</span> <span class="o">:</span> <span class="n">flight_info</span><span class="o">-></span><span class="n">endpoints</span><span class="p">())</span> <span class="p">{</span>
+ <span class="c1">// Here we assume each partition is on the same server we originally queried, but this</span>
+ <span class="c1">// isn't true in general: the server may split the query results between multiple</span>
+ <span class="c1">// other servers, which we would have to connect to.</span>
+
+ <span class="c1">// The "ticket" in the endpoint is opaque to the client. The server uses it to</span>
+ <span class="c1">// identify which part of the query results to return.</span>
+ <span class="n">ARROW_ASSIGN_OR_RAISE</span><span class="p">(</span><span class="k">auto</span> <span class="n">stream</span><span class="p">,</span> <span class="n">client</span><span class="o">-></span><span class="n">DoGet</span><span class="p">(</span><span class="n">call_options</span><span class="p">,</span> <span class="n">endpoint</span><span class="p">.</span><span class="n">ticket</span><span class="p">));</span>
+ <span class="c1">// Read all results into an Arrow Table, though we can iteratively process record</span>
+ <span class="c1">// batches as they arrive as well</span>
+ <span class="n">std</span><span class="o">::</span><span class="n">shared_ptr</span><span class="o"><</span><span class="n">arrow</span><span class="o">::</span><span class="n">Table</span><span class="o">></span> <span class="n">table</span><span class="p">;</span>
+ <span class="n">ARROW_RETURN_NOT_OK</span><span class="p">(</span><span class="n">stream</span><span class="o">-></span><span class="n">ReadAll</span><span class="p">(</span><span class="o">&</span><span class="n">table</span><span class="p">));</span>
+ <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Read one partition:"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
+ <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">table</span><span class="o">-></span><span class="n">ToString</span><span class="p">()</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
+<span class="p">}</span>
+</code></pre></div></div>
+
+<p>The full source is <a href="https://github.com/apache/arrow/blob/master/cpp/examples/arrow/flight_sql_example.cc">available on GitHub</a>.</p>
+
+<h2 id="whats-next--getting-involved">What’s Next & Getting Involved</h2>
+
+<p>Compared to existing libraries like PyODBC, <a href="https://www.dremio.com/subsurface/arrow-flight-and-flight-sql-accelerating-data-movement/">Arrow Flight is already as much as 20x faster</a> (~00:21:00).
+Flight SQL will package these performance advantages into a standard interface, ready for clients and databases to implement.</p>
+
+<p>Further protocol refinements and extensions are expected.
+Some of this work is to make it possible to implement APIs like JDBC on top of Flight SQL; a JDBC driver is being actively worked on.
+While this again introduces the overhead of data conversion, it means a database can make itself accessible to both Arrow-native clients and traditional clients by implementing Flight SQL.
+Other improvements in the future may include Python bindings, an ODBC driver, and more.</p>
+
+<p>For anyone interested in getting involved, either as a contributor or adopter, please reach out on the <a href="/community/#mailing-lists">mailing list</a> or join the discussion on <a href="https://github.com/apache/arrow">GitHub</a>.</p>
+
+
+ </main>
+ </div>
+
+ <hr/>
+<footer class="footer">
+ <div class="row">
+ <div class="col-md-9">
+ <p>Apache Arrow, Arrow, Apache, the Apache feather logo, and the Apache Arrow project logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.</p>
+ <p>© 2016-2022 The Apache Software Foundation</p>
+ </div>
+ <div class="col-md-3">
+ <a class="d-sm-none d-md-inline pr-2" href="https://www.apache.org/events/current-event.html">
+ <img src="https://www.apache.org/events/current-event-234x60.png"/>
+ </a>
+ </div>
+ </div>
+</footer>
+
+ </div>
+</body>
+</html>
diff --git a/blog/index.html b/blog/index.html
index c6e5824..2940bec 100644
--- a/blog/index.html
+++ b/blog/index.html
@@ -226,6 +226,21 @@
<p>
<h3>
+ <a href="/blog/2022/02/16/introducing-arrow-flight-sql/">Introducing Apache Arrow Flight SQL: Accelerating Database Access</a>
+ </h3>
+
+ <p>
+ <span class="blog-list-date">
+ 16 February 2022
+ </span>
+ </p>
+ We would like to introduce Flight SQL, a new client-server protocol developed by the Apache Arrow community for interacting with SQL databases that makes use of the Arrow in-memory columnar format and the Flight RPC framework. Flight SQL aims to provide broadly similar functionality to existing APIs like JDBC and...
+ </p>
+
+
+
+ <p>
+ <h3>
<a href="/blog/2022/02/13/rust-9.0/"> February 2022 Rust Apache Arrow and Parquet Highlights</a>
</h3>
diff --git a/docs/c_glib/index.html b/docs/c_glib/index.html
index daf0202..82f4f29 100644
--- a/docs/c_glib/index.html
+++ b/docs/c_glib/index.html
@@ -20,13 +20,13 @@
<meta property="og:site_name" content="Apache Arrow" />
<meta property="og:image" content="https://arrow.apache.org/img/arrow.png" />
<meta property="og:type" content="article" />
-<meta property="article:published_time" content="2022-02-14T06:23:06-05:00" />
+<meta property="article:published_time" content="2022-02-16T07:59:05-05:00" />
<meta name="twitter:card" content="summary_large_image" />
<meta property="twitter:image" content="https://arrow.apache.org/img/arrow.png" />
<meta property="twitter:title" content="Apache Arrow GLib (C)" />
<meta name="twitter:site" content="@ApacheArrow" />
<script type="application/ld+json">
-{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2022-02-14T06:23:06-05:00","datePublished":"2022-02-14T06:23:06-05:00","description":"Apache Arrow GLib (C) Apache Arrow GLib is a wrapper library for Apache Arrow C++. Apache Arrow GLib provides C API. Apache Arrow GLib supports GObject Introspection. It means that you can create language bindings at runtime or compile time automatically. API reference manuals Apache Arrow GLib Apache Parquet GLib Gandiva GLib Plasma [...]
+{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2022-02-16T07:59:05-05:00","datePublished":"2022-02-16T07:59:05-05:00","description":"Apache Arrow GLib (C) Apache Arrow GLib is a wrapper library for Apache Arrow C++. Apache Arrow GLib provides C API. Apache Arrow GLib supports GObject Introspection. It means that you can create language bindings at runtime or compile time automatically. API reference manuals Apache Arrow GLib Apache Parquet GLib Gandiva GLib Plasma [...]
<!-- End Jekyll SEO tag -->
diff --git a/feed.xml b/feed.xml
index c0d8351..a3e1ec9 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1,4 +1,189 @@
-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.2.0">Jekyll</generator><link href="https://arrow.apache.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://arrow.apache.org/" rel="alternate" type="text/html" /><updated>2022-02-14T06:23:06-05:00</updated><id>https://arrow.apache.org/feed.xml</id><title type="html">Apache Arrow</title><subtitle>Apache Arrow is a cross-language developm [...]
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="4.2.0">Jekyll</generator><link href="https://arrow.apache.org/feed.xml" rel="self" type="application/atom+xml" /><link href="https://arrow.apache.org/" rel="alternate" type="text/html" /><updated>2022-02-16T07:59:05-05:00</updated><id>https://arrow.apache.org/feed.xml</id><title type="html">Apache Arrow</title><subtitle>Apache Arrow is a cross-language developm [...]
+
+-->
+
+<p>We would like to introduce Flight SQL, a new client-server protocol developed by the Apache Arrow community for interacting with SQL databases that makes use of the Arrow in-memory columnar format and the Flight RPC framework.</p>
+
+<p>Flight SQL aims to provide broadly similar functionality to existing APIs like JDBC and ODBC, including executing queries; creating prepared statements; and fetching metadata about the supported SQL dialect, available types, defined tables, and so on.
+By building on Apache Arrow, however, Flight SQL makes it easy for clients to talk to Arrow-native databases without converting data.
+And by using <a href="/blog/2019/10/13/introducing-arrow-flight/">Flight</a>, it provides an efficient implementation of a wire format that supports features like encryption and authentication out of the box, while allowing for further optimizations like parallel data access.</p>
+
+<p>While it can be directly used for database access, it is not a direct replacement for JDBC/ODBC. Instead, Flight SQL serves as a concrete wire protocol/driver implementation that can support a JDBC/ODBC driver and reduces implementation burden on databases.</p>
+
+<!-- mermaidjs:
+
+graph LR
+ JDBC[JDBC]
+ ODBC
+ FlightSQL[Flight SQL<br>libraries]
+ ANA[Arrow-native app]
+ DB[(Database with<br>Flight SQL endpoint)]
+
+ JDBC --> FlightSQL
+ ODBC --> FlightSQL
+ ANA --> FlightSQL
+
+ FlightSQL -->|Flight RPC| DB
+
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-jdbc-odbc.svg" alt="Illustration of where Flight SQL sits in the stack. JDBC and ODBC drivers can wrap Flight SQL, or an Arrow-native application can directly use the Flight SQL libraries. Flight SQL in turn talks over Arrow Flight to a database exposing a Flight SQL endpoint." width="90%" class="img-responsive" />
+</div>
+
+<h2 id="motivation">Motivation</h2>
+
+<p>While standards like <a href="https://docs.oracle.com/javase/8/docs/technotes/guides/jdbc/">JDBC</a> and <a href="https://docs.microsoft.com/en-us/sql/odbc/reference/odbc-overview?view=sql-server-ver15">ODBC</a> have served users well for decades, they fall short for databases and clients which wish to use Apache Arrow or columnar data in general.
+Row-based APIs like JDBC or <a href="https://www.python.org/dev/peps/pep-0249/">PEP 249</a> require transposing data in this case, and for a database which is itself columnar, this means that data has to be transposed twice—once to present it in rows for the API, and once to get it back into columns for the consumer.
+Meanwhile, while APIs like ODBC do provide bulk access to result buffers, this data must still be copied into Arrow arrays for use with the broader Arrow ecosystem, as implemented by projects like <a href="https://turbodbc.readthedocs.io/en/latest/">Turbodbc</a>.
+Flight SQL aims to get rid of these intermediate steps.</p>
+
+<p>Flight SQL means database servers can implement a standard interface that is designed around Apache Arrow and columnar data from the start.
+Just like how Arrow provides a standard in-memory format, Flight SQL saves developers from having to design and implement an entirely new wire protocol.
+As mentioned, Flight already implements features like encryption on the wire and authentication of requests, which databases do not need to re-implement.</p>
+
+<p>For clients, Flight SQL provides bulk access to query results without having to convert data from another API or format.
+Additionally, by pushing the work of implementing the wire protocol into the Flight and Flight SQL libraries, less code has to be written for each client language or driver.
+And by using Flight underneath, clients and servers can cooperate to implement optimizations like parallel data access, <a href="/blog/2019/10/13/introducing-arrow-flight/#horizontal-scalability-parallel-and-partitioned-data-access">one of the original goals of Flight itself</a>.
+Databases can return multiple “endpoints” to a Flight SQL client, which can then pull data from all of them in parallel, enabling the database backend to horizontally scale.</p>
+
+<h2 id="flight-sql-basics">Flight SQL Basics</h2>
+
+<p>Flight SQL makes full use of the Flight RPC framework and its extensibility, defining additional request/response messages via <a href="https://developers.google.com/protocol-buffers/">Protobuf</a>.
+We’ll go over the Flight SQL protocol briefly, but C++ and Java already implement clients that manage much of this work.
+The full <a href="https://github.com/apache/arrow/blob/release-7.0.0/format/FlightSql.proto">protocol</a> can be found on GitHub.</p>
+
+<p>Most requests follow this pattern:</p>
+<ol>
+ <li>The client constructs a request using one of the defined Protobuf messages.</li>
+ <li>The client sends the request via the GetSchema RPC method (to get the schema of the response) or the GetFlightInfo RPC method (to execute the request).</li>
+ <li>The client makes request(s) to the endpoints returned from GetFlightInfo to get the response.</li>
+</ol>
+
+<p>Flight SQL defines methods to query database metadata, execute queries, or manipulate prepared statements.</p>
+
+<p>Metadata requests:</p>
+<ul>
+ <li>CommandGetCatalogs: list catalogs in a database.</li>
+ <li>CommandGetCrossReference: list foreign key columns that reference a particular other table.</li>
+ <li>CommandGetDbSchemas: list schemas in a catalog.</li>
+ <li>CommandGetExportedKeys: list foreign keys referencing a table.</li>
+ <li>CommandGetImportedKeys: list foreign keys of a table.</li>
+ <li>CommandGetPrimaryKeys: list primary keys of a table.</li>
+ <li>CommandGetSqlInfo: get information about the database itself and its supported SQL dialect.</li>
+ <li>CommandGetTables: list tables in a catalog/schema.</li>
+ <li>CommandGetTableTypes: list table types supported (e.g. table, view, system table).</li>
+</ul>
+
+<p>Queries:</p>
+<ul>
+ <li>CommandStatementQuery: execute a one-off SQL query.</li>
+ <li>CommandStatementUpdate: execute a one-off SQL update query.</li>
+</ul>
+
+<p>Prepared statements:</p>
+<ul>
+ <li>ActionClosePreparedStatementRequest: close a prepared statement.</li>
+ <li>ActionCreatePreparedStatementRequest: create a new prepared statement.</li>
+ <li>CommandPreparedStatementQuery: execute a prepared statement.</li>
+ <li>CommandPreparedStatementUpdate: execute a prepared statement that updates data.</li>
+</ul>
+
+<p>For example, to list all tables:</p>
+
+<!-- mermaidjs:
+
+sequenceDiagram
+ Client->>Server: GetFlightInfo(CommandGetTables)
+ Server->>Client: FlightInfo{..., Ticket, ...}
+ Client->>Server: DoGet(Ticket)
+ Server->>Client: list of tables as Arrow data
+
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-gettables.svg" alt="Sequence diagram showing how to use CommandGetTables. First, the client calls the GetFlightInfo RPC method with a serialized CommandGetTables message as the argument. The server returns a FlightInfo message containing a Ticket message. The client then calls the DoGet RPC method with the Ticket as the argument, and gets back a stream of Arrow record batches containing the tables in the database." height="363" class="img-responsive" />
+</div>
+
+<p>To execute a query:</p>
+
+<!-- mermaidjs:
+
+sequenceDiagram
+ Client->>Server: GetFlightInfo(CommandStatementQuery)
+ Server->>Client: FlightInfo{..., Ticket, ...}
+ Client->>Server: DoGet(Ticket)
+ Server->>Client: query results as Arrow data
+
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-query.svg" alt="Sequence diagram showing how to use CommandStatementQuery. First, the client calls the GetFlightInfo RPC method with a serialized CommandStatementQuery message as the argument. This message contains the SQL query. The server returns a FlightInfo message containing a Ticket message. The client then calls the DoGet RPC method with the Ticket as the argument, and gets back a stream of Arrow record batches containing the query results." heig [...]
+</div>
+
+<p>To create and execute a prepared statement to insert rows:</p>
+
+<!-- mermaidjs:
+
+sequenceDiagram
+ Client->>Server: DoAction(ActionCreatePreparedStatementRequest)
+ Server->>Client: ActionCreatePreparedStatementResult
+ Client->>Server: DoPut(CommandPreparedStatementUpdate)
+ Client-->>Server: Arrow data representing parameter values
+ Server->>Client: DoPutUpdateResult
+ Client->>Server: DoAction(ActionClosePreparedStatementRequest)
+-->
+
+<div align="center">
+<img src="/img/20220216-flight-sql-prepared.svg" alt="Sequence diagram showing how to use ActionCreatePreparedStatementResult. First, the client calls the DoAction RPC method with a serialized ActionCreatePreparedStatementResult message as the argument. This message contains the SQL query. The server returns a serialized ActionCreatePreparedStatementResult message containing an opaque handle for the prepared statement. The client then calls the DoPut RPC method with a CommandPreparedStat [...]
+</div>
+
+<h2 id="getting-started">Getting Started</h2>
+
+<p>Note that while Flight SQL is shipping as part of Apache Arrow 7.0.0, it is still under development, and detailed documentation is forthcoming.
+However, implementations are already available in C++ and Java, which provide a low-level client that can be used as well as a server skeleton that can be implemented.</p>
+
+<p>For those interested, a <a href="https://github.com/apache/arrow/blob/release-7.0.0/java/flight/flight-sql/src/test/java/org/apache/arrow/flight/sql/example/FlightSqlExample.java">server implementation wrapping Apache Derby</a> and <a href="https://github.com/apache/arrow/blob/release-7.0.0/cpp/src/arrow/flight/sql/example/sqlite_server.h">one wrapping SQLite</a> are available in the source.
+A <a href="https://github.com/apache/arrow/blob/release-7.0.0/cpp/src/arrow/flight/sql/test_app_cli.cc">simple CLI demonstrating the client</a> is also available. Finally, we can look at a brief example of executing a query and fetching results:</p>
+
+<div class="language-cpp highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">flight</span><span class="o">::</span><span class="n">FlightCallOptions</span> <span class="n">call_options</span><span class="p">;</span>
+
+<span class="c1">// Execute the query, getting a FlightInfo describing how to fetch the results</span>
+<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Executing query: '"</span> <span class="o"><<</span> <span class="n">FLAGS_query</span> <span class="o"><<</span> <span class="s">"'"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
+<span class="n">ARROW_ASSIGN_OR_RAISE</span><span class="p">(</span><span class="n">std</span><span class="o">::</span><span class="n">unique_ptr</span><span class="o"><</span><span class="n">flight</span><span class="o">::</span><span class="n">FlightInfo</span><span class="o">></span> <span class="n">flight_info</span><span class="p">,</span>
+ <span class="n">client</span><span class="o">-></span><span class="n">Execute</span><span class="p">(</span><span class="n">call_options</span><span class="p">,</span> <span class="n">FLAGS_query</span><span class="p">));</span>
+
+<span class="c1">// Fetch each partition sequentially (though this can be done in parallel)</span>
+<span class="k">for</span> <span class="p">(</span><span class="k">const</span> <span class="n">flight</span><span class="o">::</span><span class="n">FlightEndpoint</span><span class="o">&</span> <span class="n">endpoint</span> <span class="o">:</span> <span class="n">flight_info</span><span class="o">-></span><span class="n">endpoints</span><span class="p">())</span> <span class="p">{</span>
+ <span class="c1">// Here we assume each partition is on the same server we originally queried, but this</span>
+ <span class="c1">// isn't true in general: the server may split the query results between multiple</span>
+ <span class="c1">// other servers, which we would have to connect to.</span>
+
+ <span class="c1">// The "ticket" in the endpoint is opaque to the client. The server uses it to</span>
+ <span class="c1">// identify which part of the query results to return.</span>
+ <span class="n">ARROW_ASSIGN_OR_RAISE</span><span class="p">(</span><span class="k">auto</span> <span class="n">stream</span><span class="p">,</span> <span class="n">client</span><span class="o">-></span><span class="n">DoGet</span><span class="p">(</span><span class="n">call_options</span><span class="p">,</span> <span class="n">endpoint</span><span class="p">.</span><span class="n">ticket</span><span class="p">));</span>
+ <span class="c1">// Read all results into an Arrow Table, though we can iteratively process record</span>
+ <span class="c1">// batches as they arrive as well</span>
+ <span class="n">std</span><span class="o">::</span><span class="n">shared_ptr</span><span class="o"><</span><span class="n">arrow</span><span class="o">::</span><span class="n">Table</span><span class="o">></span> <span class="n">table</span><span class="p">;</span>
+ <span class="n">ARROW_RETURN_NOT_OK</span><span class="p">(</span><span class="n">stream</span><span class="o">-></span><span class="n">ReadAll</span><span class="p">(</span><span class="o">&</span><span class="n">table</span><span class="p">));</span>
+ <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Read one partition:"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
+ <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">table</span><span class="o">-></span><span class="n">ToString</span><span class="p">()</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
+<span class="p">}</span>
+</code></pre></div></div>
+
+<p>The full source is <a href="https://github.com/apache/arrow/blob/master/cpp/examples/arrow/flight_sql_example.cc">available on GitHub</a>.</p>
+
+<h2 id="whats-next--getting-involved">What’s Next & Getting Involved</h2>
+
+<p>Compared to existing libraries like PyODBC, <a href="https://www.dremio.com/subsurface/arrow-flight-and-flight-sql-accelerating-data-movement/">Arrow Flight is already as much as 20x faster</a> (~00:21:00).
+Flight SQL will package these performance advantages into a standard interface, ready for clients and databases to implement.</p>
+
+<p>Further protocol refinements and extensions are expected.
+Some of this work is to make it possible to implement APIs like JDBC on top of Flight SQL; a JDBC driver is being actively worked on.
+While this again introduces the overhead of data conversion, it means a database can make itself accessible to both Arrow-native clients and traditional clients by implementing Flight SQL.
+Other improvements in the future may include Python bindings, an ODBC driver, and more.</p>
+
+<p>For anyone interested in getting involved, either as a contributor or adopter, please reach out on the <a href="/community/#mailing-lists">mailing list</a> or join the discussion on <a href="https://github.com/apache/arrow">GitHub</a>.</p>]]></content><author><name>José Almeida, James Duong, Vinicius Fraga, Juscelino Junior, David Li, Kyle Porter, Rafael Telles</name></author><category term="application" /><summary type="html"><![CDATA[This post introduces Arrow Flight SQL, a protocol [...]
-->
@@ -136,7 +321,7 @@ Thanks for your contributions and participation in the project!</p>
<p>Documentation has been generally improved; see the <a href="https://arrow.apache.org/cookbook/">Arrow Cookbook</a> for recipes on how to use Flight in Python and R, and a new <a href="https://github.com/apache/arrow/blob/master/cpp/examples/arrow/flight_grpc_example.cc">example</a> on how to use Flight and gRPC services on the same port.</p>
-<p>This release includes Arrow Flight SQL, a protocol for using Arrow Flight to execute queries against and fetch metadata from SQL databases. Support is included for C++ and Java (but <em>not</em> languages that bind to C++, like Python or R). A more detailed blog post is forthcoming. Note that development is ongoing and the specification is currently experimental.</p>
+<p>This release includes Arrow Flight SQL, a protocol for using Arrow Flight to execute queries against and fetch metadata from SQL databases. Support is included for C++ and Java (but <em>not</em> languages that bind to C++, like Python or R). A more detailed blog post is forthcoming (<em>EDIT</em> 2022/02/16: see the <a href="/blog/2022/02/16/introducing-arrow-flight-sql/">Flight SQL announcement</a>). Note that development is ongoing and the specification is currently experimental.</p>
<h2 id="c-notes">C++ notes</h2>
@@ -382,7 +567,7 @@ validation and has resolved all outstanding RUSTSEC issues against the
crate.</p>
<p>For additional details on the 7.0.0
-Rust implementation, please see the <a href="https://github.com/apache/arrow-rs/blob/7.0.0/CHANGELOG.md">Arrow Rust CHANGELOG</a></p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The rel [...]
+Rust implementation, please see the <a href="https://github.com/apache/arrow-rs/blob/7.0.0/CHANGELOG.md">Arrow Rust CHANGELOG</a></p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 7.0.0 release. This covers over 3 months of development work and includes 617 resolved issues from 105 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The rel [...]
-->
@@ -1792,65 +1977,4 @@ communicate safety, and a faster (but unstable) sorting kernel.</p>
<p>For additional details on the 6.0.0
Rust implementation, please see the <a href="https://github.com/apache/arrow-rs/blob/6.0.0/CHANGELOG.md">Arrow Rust
-CHANGELOG</a></p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 6.0.0 release. This covers over 3 months of development work and includes 572 resolved issues from 77 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and only expose selected highlights of the release. Many other bugfixes and impro [...]
-
--->
-
-<p>Ballista extends DataFusion to provide support for distributed queries. This is the first release of Ballista since
-the project was <a href="https://arrow.apache.org/blog/2021/04/12/ballista-donation/">donated</a> to the Apache Arrow project
-and includes 80 commits from 11 contributors.</p>
-
-<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>git shortlog -sn 4.0.0..5.0.0 ballista/rust/client ballista/rust/core ballista/rust/executor ballista/rust/scheduler
- 27 Andy Grove
- 15 Jiayu Liu
- 12 Andrew Lamb
- 8 Ximo Guanter
- 6 Daniël Heres
- 5 QP Hou
- 2 Jorge Leitao
- 1 Javier Goday
- 1 K.I. (Dennis) Jung
- 1 Mike Seddon
- 1 sathis
-</code></pre></div></div>
-
-<!--
-$ git log --pretty=oneline 4.0.0..5.0.0 ballista/rust/client ballista/rust/core ballista/rust/executor ballista/rust/scheduler ballista-examples/ | wc -l
-80
--->
-
-<p>The release notes below are not exhaustive and only expose selected highlights of the release. Many other bug fixes
-and improvements have been made: we refer you to the <a href="https://github.com/apache/arrow-datafusion/blob/5.0.0/ballista/CHANGELOG.md">complete changelog</a>.</p>
-
-<h1 id="performance-and-scalability">Performance and Scalability</h1>
-
-<p>Ballista is now capable of running complex SQL queries at scale and supports scalable distributed joins. We have been
-benchmarking using individual queries from the TPC-H benchmark at scale factors up to 1000 (1 TB). When running against
-CSV files, performance is generally very close to DataFusion, and significantly faster in some cases due to the fact
-that the scheduler limits the number of concurrent tasks that run at any given time. Performance against large Parquet
-datasets is currently non ideal due to some issues (<a href="https://github.com/apache/arrow-datafusion/issues/867">#867</a>,
-<a href="https://github.com/apache/arrow-datafusion/issues/868">#868</a>) that we hope to resolve for the next release.</p>
-
-<h1 id="new-features">New Features</h1>
-
-<p>The main new features in this release are:</p>
-
-<ul>
- <li>Ballista queries can now be executed by calling DataFrame.collect()</li>
- <li>The shuffle mechanism has been re-implemented</li>
- <li>Distributed hash-partitioned joins are now supported</li>
- <li>Keda autoscaling is supported</li>
-</ul>
-
-<p>To get started with Ballista, refer to the <a href="https://docs.rs/ballista/0.5.0/ballista/">crate documentation</a>.</p>
-
-<p>Now that the basic functionality is in place, the focus for the next release will be to improve the performance and
-scalability as well as improving the documentation.</p>
-
-<h1 id="how-to-get-involved">How to Get Involved</h1>
-
-<p>If you are interested in contributing to Ballista, we would love to have you! You
-can help by trying out Ballista on some of your own data and projects and filing bug reports and helping to
-improve the documentation, or contribute to the documentation, tests or code. A list of open issues suitable for
-beginners is <a href="https://github.com/apache/arrow-datafusion/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22">here</a>
-and the full list is <a href="https://github.com/apache/arrow-datafusion/issues">here</a>.</p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[Ballista extends DataFusion to provide support for distributed queries. This is the first release of Ballista since the project was donated to the Apache Arrow project and includes 80 commits from 11 contributors. git shortlog -sn 4.0.0..5.0.0 ballista/rust/client ballista/rust/core ballista/ru [...]
\ No newline at end of file
+CHANGELOG</a></p>]]></content><author><name>pmc</name></author><category term="release" /><summary type="html"><![CDATA[The Apache Arrow team is pleased to announce the 6.0.0 release. This covers over 3 months of development work and includes 572 resolved issues from 77 distinct contributors. See the Install Page to learn how to get the libraries for your platform. The release notes below are not exhaustive and only expose selected highlights of the release. Many other bugfixes and impro [...]
\ No newline at end of file
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new file mode 100644
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new file mode 100644
index 0000000..aa63f9c
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+++ b/img/20220216-flight-sql-jdbc-odbc.svg
@@ -0,0 +1 @@
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new file mode 100644
index 0000000..3e1af8d
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@@ -0,0 +1 @@
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new file mode 100644
index 0000000..b159a75
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@@ -0,0 +1 @@
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diff --git a/release/0.1.0.html b/release/0.1.0.html
index 0e44aba..4608e7c 100644
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index 684a93e..1ab5f22 100644
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diff --git a/release/7.0.0.html b/release/7.0.0.html
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