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commit ad43bac16288cec9a8b0f0936c6532cb6ec70184
Author: Etienne Chauchot <echauc...@apache.org>
AuthorDate: Tue May 9 10:28:18 2023 +0200
Rebuild website
---
.../index.html | 1184 ++++++++++++++++++++
1 file changed, 1184 insertions(+)
diff --git
a/content/2023/05/09/howto-migrate-a-real-life-batch-pipeline-from-the-dataset-api-to-the-datastream-api/index.html
b/content/2023/05/09/howto-migrate-a-real-life-batch-pipeline-from-the-dataset-api-to-the-datastream-api/index.html
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@@ -0,0 +1,1184 @@
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+<meta name="description" content="Introduction # The Flink community has been
deprecating the DataSet API since version 1.12 as part of the work on FLIP-131:
Consolidate the user-facing Dataflow SDKs/APIs (and deprecate the DataSet API)
. This blog article illustrates the migration of a real-life batch DataSet
pipeline to a batch DataStream pipeline. All the code presented in this article
is available in the tpcds-benchmark-flink repo. The use case shown here is
extracted from a broader [...]
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DataStream API" />
+<meta property="og:description" content="Introduction # The Flink community
has been deprecating the DataSet API since version 1.12 as part of the work on
FLIP-131: Consolidate the user-facing Dataflow SDKs/APIs (and deprecate the
DataSet API) . This blog article illustrates the migration of a real-life batch
DataSet pipeline to a batch DataStream pipeline. All the code presented in this
article is available in the tpcds-benchmark-flink repo. The use case shown here
is extracted from a b [...]
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+ <strong>Howto migrate a real-life batch pipeline from the DataSet API to the
DataStream API</strong>
+
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+
+<nav id="TableOfContents"><h3>On This Page <button class="toc"
onclick="collapseToc()"><i class="fa fa-compress"
aria-hidden="true"></i></button></h3>
+ <ul>
+ <li><a href="#introduction">Introduction</a></li>
+ <li><a href="#what-is-tpcds">What is TPCDS?</a></li>
+ <li><a href="#chosen-tpcds-query">Chosen TPCDS query</a></li>
+ <li><a href="#the-initial-dataset-pipeline">The initial DataSet
pipeline</a></li>
+ <li><a
href="#migrating-the-dataset-pipeline-to-a-datastream-pipeline">Migrating the
DataSet pipeline to a DataStream pipeline</a>
+ <ul>
+ <li><a
href="#setting-the-execution-environmenthttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval90-l96"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L90-L96";>Setting
the execution environment</a></a></li>
+ <li><a href="#using-the-streaming-sources-and-datasets">Using the
streaming sources and datasets</a></li>
+ <li><a
href="#migrating-the-join-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval129-l135"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L129-L135";>Migrating
the join operation</a></a></li>
+ <li><a
href="#migrating-the-group-by-and-reduce-sum-operationshttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval145-l169"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L145-L169";>Migrating
the group by and reduce (sum) operations</a></a></li>
+ <li><a
href="#migrating-the-order-by-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval171-l211"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L171-L211";>Migrating
the order by operation</a></a></li>
+ <li><a
href="#migrating-the-limit-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval213-l223"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L213-L223";>Migrating
the limit operation</a></a></li>
+ <li><a
href="#migrating-the-sink-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval225-l236"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L225-L236";>Migrating
the sink operation</a></a></li>
+ </ul>
+ </li>
+ <li><a href="#conclusion">Conclusion</a></li>
+ </ul>
+</nav>
+
+
+ </aside>
+
+
+ </header>
+
+
+
+
+
+
+
+<article class="markdown">
+ <h1>
+ <a
href="/2023/05/09/howto-migrate-a-real-life-batch-pipeline-from-the-dataset-api-to-the-datastream-api/">Howto
migrate a real-life batch pipeline from the DataSet API to the DataStream
API</a>
+ </h1>
+
+ May 9, 2023 -
+
+
+
+ Etienne Chauchot
+
+ <a href="https://twitter.com/echauchot";>(@echauchot)</a>
+
+
+
+
+ <p><h2 id="introduction">
+ Introduction
+ <a class="anchor" href="#introduction">#</a>
+</h2>
+<p>The Flink community has been deprecating the DataSet API since version 1.12
as part of the work on
+<a
href="https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=158866741";>FLIP-131:
Consolidate the user-facing Dataflow SDKs/APIs (and deprecate the DataSet
API)</a>
+.
+This blog article illustrates the migration of a real-life batch DataSet
pipeline to a batch
+DataStream pipeline.
+All the code presented in this article is available in
+the <a
href="https://github.com/echauchot/tpcds-benchmark-flink";>tpcds-benchmark-flink
repo</a>.
+The use case shown here is extracted from a broader work comparing Flink
performances of different
+APIs
+by implementing <a href="https://www.tpc.org/tpcds/";>TPCDS</a> queries using
these APIs.</p>
+<h2 id="what-is-tpcds">
+ What is TPCDS?
+ <a class="anchor" href="#what-is-tpcds">#</a>
+</h2>
+<p>TPC-DS is a decision support benchmark that models several generally
applicable aspects of a
+decision support system. The purpose of TPCDS benchmarks is to provide
relevant, objective
+performance data of Big Data engines to industry users.</p>
+<h2 id="chosen-tpcds-query">
+ Chosen TPCDS query
+ <a class="anchor" href="#chosen-tpcds-query">#</a>
+</h2>
+<p>The chosen query for this article is <strong>Query3</strong> because it
contains all the more common analytics
+operators (filter, join, aggregation, group by, order by, limit). It
represents an analytic query on
+store sales. Its SQL code is presented here:</p>
+<p><code>SELECT dt.d_year, item.i_brand_id brand_id, item.i_brand
brand,SUM(ss_ext_sales_price) sum_agg FROM date_dim dt, store_sales, item
WHERE dt.d_date_sk = store_sales.ss_sold_date_sk AND store_sales.ss_item_sk =
item.i_item_sk AND item.i_manufact_id = 128 AND dt.d_moy=11 GROUP BY dt.d_year,
item.i_brand, item.i_brand_id ORDER BY dt.d_year, sum_agg desc, brand_id LIMIT
100</code></p>
+<h2 id="the-initial-dataset-pipeline">
+ The initial DataSet pipeline
+ <a class="anchor" href="#the-initial-dataset-pipeline">#</a>
+</h2>
+<p>The pipeline we are migrating
+is <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDataset.java";>this</a>
+batch pipeline that implements the above query using the DataSet API
+and <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/types/Row.html";>Row</a>
+as dataset element type.</p>
+<h2 id="migrating-the-dataset-pipeline-to-a-datastream-pipeline">
+ Migrating the DataSet pipeline to a DataStream pipeline
+ <a class="anchor"
href="#migrating-the-dataset-pipeline-to-a-datastream-pipeline">#</a>
+</h2>
+<p>Instead of going through all of the code which is
+available <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java";>here</a>
+we will rather focus on some key areas of the migration. The code is based on
the latest release
+of Flink at the time this article was written: version 1.16.0.</p>
+<p>DataStream is a unified API that allows to run pipelines in both batch and
streaming modes. To
+execute a DataStream pipeline in batch mode, it is not enough to set the
execution mode in the Flink
+execution environment, it is also needed to migrate some operations. Indeed,
the DataStream API
+semantics are the ones of a streaming pipeline. The arriving data is thus
considered infinite. So,
+compared to the DataSet API which operates on finite data, there are
adaptations to be made on some
+operations.</p>
+<h3
id="setting-the-execution-environmenthttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval90-l96">
+ <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L90-L96";>Setting
the execution environment</a>
+ <a class="anchor"
href="#setting-the-execution-environmenthttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval90-l96">#</a>
+</h3>
+<p>We start by moving
+from <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/api/java/ExecutionEnvironment.html";>ExecutionEnvironment</a>
+to <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/environment/StreamExecutionEnvironment.html";>StreamExecutionEnvironment</a>
+. Then, as the source in this pipeline is bounded, we can use either the
default
+streaming <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/datastream/execution_mode//";>execution
mode</a>
+or the batch mode. In batch mode the tasks of the job can be separated into
stages that can be
+executed one after another. In streaming mode all tasks need to be running all
the time and records
+are sent to downstream tasks as soon as they are available.</p>
+<p>Here we keep the default streaming mode that gives good performance on this
pipeline and that would
+allow to run the same pipeline with no change on an unbounded source.</p>
+<h3 id="using-the-streaming-sources-and-datasets">
+ Using the streaming sources and datasets
+ <a class="anchor" href="#using-the-streaming-sources-and-datasets">#</a>
+</h3>
+<p><strong>Sources</strong>: <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/api/java/operators/DataSource.html";>DataSource<T></a>
+becomes <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/datastream/DataStreamSource.html";>DataStreamSource<T></a>
+after the call to <em>env.createInput()</em>.</p>
+<p><strong>Datasets</strong>: <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/api/java/DataSet.html";>DataSet<T></a>
+are
+now <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/datastream/DataStream.html";>DataStream<T></a>
+and subclasses.</p>
+<h3
id="migrating-the-join-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval129-l135">
+ <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L129-L135";>Migrating
the join operation</a>
+ <a class="anchor"
href="#migrating-the-join-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval129-l135">#</a>
+</h3>
+<p>The DataStream join operator does not yet support aggregations in batch
mode (
+see <a
href="https://issues.apache.org/jira/browse/FLINK-22587";>FLINK-22587</a> for
details). Basically, the
+problem is with the trigger of the
+default <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/windowing/windows/GlobalWindow.html";>GlobalWindow</a>
+which never fires so the records are never output. We will workaround this
problem by applying a
+custom <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L246-L280";>EndOfStream</a>
+window. It is a window assigner that assigns all the records to a
+single <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/windowing/windows/TimeWindow.html";>TimeWindow</a>
+. So, like for the GlobalWindow, all the records are assigned to the same
window except that this
+window’s trigger is based on the end of the window (which is set to
<em>Long.MAX_VALUE</em>). As we are on
+a bounded source, at some point the watermark will advance to +INFINITY
(Long.MAX_VALUE) and will
+thus cross the end of the time window and consequently fire the trigger and
output the records.</p>
+<p>Now that we have a working triggering, we need to call a standard join with
the <em>Row::join</em>
+function.</p>
+<h3
id="migrating-the-group-by-and-reduce-sum-operationshttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval145-l169">
+ <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L145-L169";>Migrating
the group by and reduce (sum) operations</a>
+ <a class="anchor"
href="#migrating-the-group-by-and-reduce-sum-operationshttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval145-l169">#</a>
+</h3>
+<p>DataStream API has no
+more <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/api/java/DataSet.html#groupBy-org.apache.flink.api.java.functions.KeySelector-";>groupBy()</a>
+method, we now use
+the <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/datastream/DataStream.html#keyBy-org.apache.flink.api.java.functions.KeySelector-";>keyBy()</a>
+method. An aggregation downstream will be applied on elements with the same
key exactly as
+a <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/api/common/functions/GroupReduceFunction.html";>GroupReduceFunction</a>
+would have done on a DataSet except it will not need to materialize the
collection of data. Indeed, the following
+operator is a reducer: the summing operation downstream is still done through
+a <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/api/common/functions/ReduceFunction.html";>ReduceFunction</a>
+but this time the operator reduces the elements incrementally instead of
receiving the rows as a
+Collection. To make the sum we store in the reduced row the partially
aggregated sum. Due to incremental reduce,
+we also need to distinguish if we received an already reduced row (in that
case, we read the
+partially aggregated sum) or a fresh row (in that case we just read the
corresponding price field).
+Also, please note that, as in the join case, we need to specify windowing for
the aggregation.</p>
+<h3
id="migrating-the-order-by-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval171-l211">
+ <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L171-L211";>Migrating
the order by operation</a>
+ <a class="anchor"
href="#migrating-the-order-by-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval171-l211">#</a>
+</h3>
+<p>The sort of the datastream is done by applying
+a <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/functions/KeyedProcessFunction.html";>KeyedProcessFunction</a>
+.</p>
+<p>But, as said above, the DataStream semantics are the ones of a streaming
pipeline. The arriving data
+is thus considered infinite. As such we need to “divide” the data
to have output times. For that we
+need to set a timer to output the resulting data. We <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L188";>set
a timer to fire at the end of the EndOfStream window</a>
+meaning that the timer will fire at the end of the batch.</p>
+<p>To sort the data, we store the incoming rows inside
+a <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/api/common/state/ListState.html";>ListState</a>
+and sort them at output time, when the timer fires in
+the <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/streaming/api/functions/KeyedProcessFunction.html#onTimer-long-org.apache.flink.streaming.api.functions.KeyedProcessFunction.OnTimerContext-org.apache.flink.util.Collector-";>onTimer()</a>
+callback.</p>
+<p>Another thing: to be able to use Flink state, we need to key the datastream
beforehand, even if
+there
+is no group by key because Flink state is designed per-key. Thus, we key by a
fake static key so
+that there is a single state.</p>
+<h3
id="migrating-the-limit-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval213-l223">
+ <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L213-L223";>Migrating
the limit operation</a>
+ <a class="anchor"
href="#migrating-the-limit-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval213-l223">#</a>
+</h3>
+<p>As all the elements of the DataStream were keyed by the same
“0” key, they are kept in the same "
+group". So we can implement the SQL LIMIT with
+a <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/streaming/api/functions/ProcessFunction.html";>ProcessFunction</a>
+with a counter that will output only the first 100 elements.</p>
+<h3
id="migrating-the-sink-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval225-l236">
+ <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L225-L236";>Migrating
the sink operation</a>
+ <a class="anchor"
href="#migrating-the-sink-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval225-l236">#</a>
+</h3>
+<p>As with sources, there were big changes in sinks with recent versions of
Flink. We now use
+the <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/api/connector/sink2/Sink.html";>Sink
interface</a>
+that requires
+an <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/api/common/serialization/Encoder.html";>Encoder</a>
+. But the resulting code is very similar to the one using the DataSet API.
It’s only
+that <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/api/java/org/apache/flink/api/common/serialization/Encoder.html#encode-IN-java.io.OutputStream-";>Encoder#encode()</a>
+method writes bytes
+when <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.12/api/java/org/apache/flink/api/java/io/TextOutputFormat.TextFormatter.html#format-IN-";>TextOutputFormat.TextFormatter#format()</a>
+wrote Strings.</p>
+<h2 id="conclusion">
+ Conclusion
+ <a class="anchor" href="#conclusion">#</a>
+</h2>
+<p>As you saw for the migration of the join operation, the new unified
DataStream API has some
+limitations left in batch mode. In addition, the order by and limit resulting
code is quite manual
+and requires the help of the Flink state API for the migration. For all these
reasons, the Flink
+community recommends to use Flink SQL for batch pipelines. It results in much
simpler code, good
+performance and out-of-the-box analytics capabilities. You could find the
equivalent Query3 code
+that uses
+the <a
href="https://nightlies.apache.org/flink/flink-docs-release-1.16/docs/dev/table/overview/";>Flink
SQL/Table API</a>
+in
+the <a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkSQLCSV.java";>Query3ViaFlinkSQLCSV
class</a>
+.</p>
+</p>
+</article>
+
+
+
+ <footer class="book-footer">
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+
+
+
+<nav id="TableOfContents"><h3>On This Page <button class="toc"
onclick="collapseToc()"><i class="fa fa-compress"
aria-hidden="true"></i></button></h3>
+ <ul>
+ <li><a href="#introduction">Introduction</a></li>
+ <li><a href="#what-is-tpcds">What is TPCDS?</a></li>
+ <li><a href="#chosen-tpcds-query">Chosen TPCDS query</a></li>
+ <li><a href="#the-initial-dataset-pipeline">The initial DataSet
pipeline</a></li>
+ <li><a
href="#migrating-the-dataset-pipeline-to-a-datastream-pipeline">Migrating the
DataSet pipeline to a DataStream pipeline</a>
+ <ul>
+ <li><a
href="#setting-the-execution-environmenthttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval90-l96"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L90-L96";>Setting
the execution environment</a></a></li>
+ <li><a href="#using-the-streaming-sources-and-datasets">Using the
streaming sources and datasets</a></li>
+ <li><a
href="#migrating-the-join-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3fsrcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval129-l135"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/4273a3bc45d6e4fbdd5fa531fe48f85b8d0a9d3f/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L129-L135";>Migrating
the join operation</a></a></li>
+ <li><a
href="#migrating-the-group-by-and-reduce-sum-operationshttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval145-l169"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L145-L169";>Migrating
the group by and reduce (sum) operations</a></a></li>
+ <li><a
href="#migrating-the-order-by-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval171-l211"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L171-L211";>Migrating
the order by operation</a></a></li>
+ <li><a
href="#migrating-the-limit-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval213-l223"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L213-L223";>Migrating
the limit operation</a></a></li>
+ <li><a
href="#migrating-the-sink-operationhttpsgithubcomechauchottpcds-benchmark-flinkblob9589c7c74e7152badee8400d775b4af7a998e487srcmainjavaorgexampletpcdsflinkquery3viaflinkrowdatastreamjaval225-l236"><a
href="https://github.com/echauchot/tpcds-benchmark-flink/blob/9589c7c74e7152badee8400d775b4af7a998e487/src/main/java/org/example/tpcds/flink/Query3ViaFlinkRowDatastream.java#L225-L236";>Migrating
the sink operation</a></a></li>
+ </ul>
+ </li>
+ <li><a href="#conclusion">Conclusion</a></li>
+ </ul>
+</nav>
+
+
+ </aside>
+ <aside class="expand-toc">
+ <button class="toc" onclick="expandToc()">
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