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class=section-nav-list-title>Concepts</span><ul class=section-nav-list><li><a href=/documentation/basics/>Basics of the Beam model</a></li><li><a href=/documentation/runtime/model/>How Beam executes a pipeline</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Beam programming guide</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/>Overview</a></li><li><a href=/documentation/programming-guide/#creating-a-pipeline>Pipelines</a></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>PCollections</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#pcollections>Creating a PCollection</a></li><li><a href=/documentation/programming-guide/#pcollection-characteristics>PCollection characteristics</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Transforms</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#applying-transforms>Applying transforms</a></li><li><span class=section-nav-list-title>Core Beam transforms</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#pardo>ParDo</a></li><li><a href=/documentation/programming-guide/#groupbykey>GroupByKey</a></li><li><a href=/documentation/programming-guide/#cogroupbykey>CoGroupByKey</a></li><li><a href=/documentation/programming-guide/#combine>Combine</a></li><li><a href=/documentation/programming-guide/#flatten>Flatten</a></li><li><a href=/documentation/programming-guide/#partition>Partition</a></li></ul></li><li><a href=/documentation/programming-guide/#requirements-for-writing-user-code-for-beam-transforms>Requirements for user code</a></li><li><a href=/documentation/programming-guide/#side-inputs>Side inputs</a></li><li><a href=/documentation/programming-guide/#additional-outputs>Additional outputs</a></li><li><a href=/documentation/programming-guide/#composite-transforms>Composite transforms</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Pipeline I/O</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#pipeline-io>Using I/O transforms</a></li><li><a href=/documentation/io/connectors/>I/O connectors</a></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>I/O connector guides</span><ul class=section-nav-list><li><a href=/documentation/io/built-in/parquet/>Apache Parquet I/O connector</a></li><li><a href=/documentation/io/built-in/hadoop/>Hadoop Input/Output Format IO</a></li><li><a href=/documentation/io/built-in/hcatalog/>HCatalog IO</a></li><li><a href=/documentation/io/built-in/google-bigquery/>Google BigQuery I/O connector</a></li><li><a href=/documentation/io/built-in/snowflake/>Snowflake I/O connector</a></li><li><a href=/documentation/io/built-in/cdap/>CDAP I/O connector</a></li><li><a href=/documentation/io/built-in/sparkreceiver/>Spark Receiver I/O connector</a></li><li><a href=/documentation/io/built-in/singlestore/>SingleStoreDB I/O connector</a></li><li><a href=/documentation/io/built-in/webapis/>Web APIs I/O connector</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Developing new I/O connectors</span><ul class=section-nav-list><li><a href=/documentation/io/developing-io-overview/>Overview: Developing connectors</a></li><li><a href=/documentation/io/developing-io-java/>Developing connectors (Java)</a></li><li><a href=/documentation/io/developing-io-python/>Developing connectors (Python)</a></li><li><a href=/documentation/io/io-standards/>I/O Standards</a></li></ul></li><li><a href=/documentation/io/testing/>Testing I/O transforms</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Schemas</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#what-is-a-schema>What is a schema</a></li><li><a href=/documentation/programming-guide/#schemas-for-pl-types>Schemas for programming language types</a></li><li><a href=/documentation/programming-guide/#schema-definition>Schema definition</a></li><li><a href=/documentation/programming-guide/#logical-types>Logical types</a></li><li><a href=/documentation/programming-guide/#creating-schemas>Creating schemas</a></li><li><a href=/documentation/programming-guide/#using-schemas>Using schemas</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Data encoding and type safety</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#data-encoding-and-type-safety>Data encoding basics</a></li><li><a href=/documentation/programming-guide/#specifying-coders>Specifying coders</a></li><li><a href=/documentation/programming-guide/#default-coders-and-the-coderregistry>Default coders and the CoderRegistry</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Windowing</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#windowing>Windowing basics</a></li><li><a href=/documentation/programming-guide/#provided-windowing-functions>Provided windowing functions</a></li><li><a href=/documentation/programming-guide/#setting-your-pcollections-windowing-function>Setting your PCollection’s windowing function</a></li><li><a href=/documentation/programming-guide/#watermarks-and-late-data>Watermarks and late data</a></li><li><a href=/documentation/programming-guide/#adding-timestamps-to-a-pcollections-elements>Adding timestamps to a PCollection’s elements</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Triggers</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#triggers>Trigger basics</a></li><li><a href=/documentation/programming-guide/#event-time-triggers>Event time triggers and the default trigger</a></li><li><a href=/documentation/programming-guide/#processing-time-triggers>Processing time triggers</a></li><li><a href=/documentation/programming-guide/#data-driven-triggers>Data-driven triggers</a></li><li><a href=/documentation/programming-guide/#setting-a-trigger>Setting a trigger</a></li><li><a href=/documentation/programming-guide/#composite-triggers>Composite triggers</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Metrics</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#metrics>Metrics basics</a></li><li><a href=/documentation/programming-guide/#types-of-metrics>Types of metrics</a></li><li><a href=/documentation/programming-guide/#querying-metrics>Querying metrics</a></li><li><a href=/documentation/programming-guide/#using-metrics>Using metrics in pipeline</a></li><li><a href=/documentation/programming-guide/#export-metrics>Export metrics</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>State and Timers</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#types-of-state>Types of state</a></li><li><a href=/documentation/programming-guide/#deferred-state-reads>Deferred state reads</a></li><li><a href=/documentation/programming-guide/#timers>Timers</a></li><li><a href=/documentation/programming-guide/#garbage-collecting-state>Garbage collecting state</a></li><li><a href=/documentation/programming-guide/#state-timers-examples>State and timers examples</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Splittable DoFns</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#sdf-basics>Basics</a></li><li><a href=/documentation/programming-guide/#sizing-and-progress>Sizing and progress</a></li><li><a href=/documentation/programming-guide/#user-initiated-checkpoint>User-initiated checkpoint</a></li><li><a href=/documentation/programming-guide/#runner-initiated-split>Runner initiated split</a></li><li><a href=/documentation/programming-guide/#watermark-estimation>Watermark estimation</a></li><li><a href=/documentation/programming-guide/#truncating-during-drain>Truncating during drain</a></li><li><a href=/documentation/programming-guide/#bundle-finalization>Bundle finalization</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Multi-language Pipelines</span><ul class=section-nav-list><li><a href=/documentation/programming-guide/#create-x-lang-transforms>Creating cross-language transforms</a></li><li><a href=/documentation/programming-guide/#use-x-lang-transforms>Using cross-language transforms</a></li><li><a href=/documentation/programming-guide/#x-lang-transform-runner-support>Runner Support</a></li></ul></li><li><a href=/documentation/programming-guide/#batched-dofns>Batched DoFns</a></li><li><a href=/documentation/programming-guide/#transform-service>Transform service</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Pipeline development lifecycle</span><ul class=section-nav-list><li><a href=/documentation/pipelines/design-your-pipeline/>Design Your Pipeline</a></li><li><a href=/documentation/pipelines/create-your-pipeline/>Create Your Pipeline</a></li><li><a href=/documentation/pipelines/test-your-pipeline/>Test Your Pipeline</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Common pipeline patterns</span><ul class=section-nav-list><li><a href=/documentation/patterns/overview/>Overview</a></li><li><a href=/documentation/patterns/file-processing/>File processing</a></li><li><a href=/documentation/patterns/side-inputs/>Side inputs</a></li><li><a href=/documentation/patterns/pipeline-options/>Pipeline options</a></li><li><a href=/documentation/patterns/custom-io/>Custom I/O</a></li><li><a href=/documentation/patterns/custom-windows/>Custom windows</a></li><li><a href=/documentation/patterns/bigqueryio/>BigQueryIO</a></li><li><a href=/documentation/patterns/ai-platform/>AI Platform</a></li><li><a href=/documentation/patterns/schema/>Schema</a></li><li><a href=/documentation/patterns/bqml/>BigQuery ML</a></li><li><a href=/documentation/patterns/grouping-elements-for-efficient-external-service-calls/>Grouping elements for efficient external service calls</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>AI/ML pipelines</span><ul class=section-nav-list><li><a href=/documentation/ml/overview/>Get started with AI/ML</a></li><li><a href=/documentation/ml/about-ml/>About Beam ML</a></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Prediction and inference</span><ul class=section-nav-list><li><a href=/documentation/ml/inference-overview/>Overview</a></li><li><a href=/documentation/ml/multi-model-pipelines/>Build a pipeline with multiple models</a></li><li><a href=/documentation/ml/tensorrt-runinference>Build a custom model handler with TensorRT</a></li><li><a href=/documentation/ml/large-language-modeling>Use LLM inference</a></li><li><a href=/documentation/ml/multi-language-inference/>Build a multi-language inference pipeline</a></li><li><a href=/documentation/ml/side-input-updates/>Update your model in production</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Data processing</span><ul class=section-nav-list><li><a href=/documentation/ml/preprocess-data/>Preprocess data</a></li><li><a href=/documentation/ml/data-processing/>Explore your data</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Workflow orchestration</span><ul class=section-nav-list><li><a href=/documentation/ml/orchestration/>Use ML-OPS workflow orchestrators</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Model training</span><ul class=section-nav-list><li><a href=/documentation/ml/per-entity-training>Per-entity training</a></li><li><a href=/documentation/ml/online-clustering/>Online clustering</a></li><li><a href=/documentation/ml/model-evaluation/>ML model evaluation</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Use cases</span><ul class=section-nav-list><li><a href=/documentation/ml/anomaly-detection/>Build an anomaly detection pipeline</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Reference</span><ul class=section-nav-list><li><a href=/documentation/ml/runinference-metrics/>RunInference metrics</a></li><li><a href=/documentation/ml/model-evaluation/>Model validation</a></li></ul></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Runtime systems</span><ul class=section-nav-list><li><a href=/documentation/runtime/environments/>Container environments</a></li><li><a href=/documentation/runtime/resource-hints/>Resource hints</a></li><li><a href=/documentation/runtime/sdk-harness-config/>SDK Harness Configuration</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Transform catalog</span><ul class=section-nav-list><li class=section-nav-item--collapsible><span class=section-nav-list-title>Python</span><ul class=section-nav-list><li><a href=/documentation/transforms/python/overview/>Overview</a></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Element-wise</span><ul class=section-nav-list><li class=section-nav-item--collapsible><span class=section-nav-list-title>Enrichment</span><ul class=section-nav-list><li><a href=/documentation/transforms/python/elementwise/enrichment/>Overview</a></li><li><a href=/documentation/transforms/python/elementwise/enrichment-bigtable/>Bigtable example</a></li><li><a href=/documentation/transforms/python/elementwise/enrichment-vertexai/>Vertex AI Feature Store examples</a></li></ul></li><li><a href=/documentation/transforms/python/elementwise/filter/>Filter</a></li><li><a href=/documentation/transforms/python/elementwise/flatmap/>FlatMap</a></li><li><a href=/documentation/transforms/python/elementwise/keys/>Keys</a></li><li><a href=/documentation/transforms/python/elementwise/kvswap/>KvSwap</a></li><li><a href=/documentation/transforms/python/elementwise/map/>Map</a></li><li><a href=/documentation/transforms/python/elementwise/mltransform/>MLTransform</a></li><li><a href=/documentation/transforms/python/elementwise/pardo/>ParDo</a></li><li><a href=/documentation/transforms/python/elementwise/partition/>Partition</a></li><li><a href=/documentation/transforms/python/elementwise/regex/>Regex</a></li><li><a href=/documentation/transforms/python/elementwise/reify/>Reify</a></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>RunInference</span><ul class=section-nav-list><li><a href=/documentation/transforms/python/elementwise/runinference/>Overview</a></li><li><a href=/documentation/transforms/python/elementwise/runinference-pytorch/>PyTorch examples</a></li><li><a href=/documentation/transforms/python/elementwise/runinference-sklearn/>Sklearn examples</a></li></ul></li><li><a href=/documentation/transforms/python/elementwise/tostring/>ToString</a></li><li><a href=/documentation/transforms/python/elementwise/values/>Values</a></li><li><a href=/documentation/transforms/python/elementwise/withtimestamps/>WithTimestamps</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Aggregation</span><ul class=section-nav-list><li><a href=/documentation/transforms/python/aggregation/approximatequantiles/>ApproximateQuantiles</a></li><li><a href=/documentation/transforms/python/aggregation/approximateunique/>ApproximateUnique</a></li><li><a href=/documentation/transforms/python/aggregation/cogroupbykey/>CoGroupByKey</a></li><li><a href=/documentation/transforms/python/aggregation/combineglobally/>CombineGlobally</a></li><li><a href=/documentation/transforms/python/aggregation/combineperkey/>CombinePerKey</a></li><li><a href=/documentation/transforms/python/aggregation/combinevalues/>CombineValues</a></li><li><a href=/documentation/transforms/python/aggregation/count/>Count</a></li><li><a href=/documentation/transforms/python/aggregation/distinct/>Distinct</a></li><li><a href=/documentation/transforms/python/aggregation/groupby/>GroupBy</a></li><li><a href=/documentation/transforms/python/aggregation/groupbykey/>GroupByKey</a></li><li><a href=/documentation/transforms/python/aggregation/groupintobatches/>GroupIntoBatches</a></li><li><a href=/documentation/transforms/python/aggregation/latest/>Latest</a></li><li><a href=/documentation/transforms/python/aggregation/max/>Max</a></li><li><a href=/documentation/transforms/python/aggregation/mean/>Mean</a></li><li><a href=/documentation/transforms/python/aggregation/min/>Min</a></li><li><a href=/documentation/transforms/python/aggregation/sample/>Sample</a></li><li><a href=/documentation/transforms/python/aggregation/sum/>Sum</a></li><li><a href=/documentation/transforms/python/aggregation/top/>Top</a></li><li><a href=/documentation/transforms/python/aggregation/tolist/>ToList</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Other</span><ul class=section-nav-list><li><a href=/documentation/transforms/python/other/create/>Create</a></li><li><a href=/documentation/transforms/python/other/flatten/>Flatten</a></li><li><a href=/documentation/transforms/python/other/reshuffle/>Reshuffle</a></li><li><a href=/documentation/transforms/python/other/windowinto/>WindowInto</a></li></ul></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Java</span><ul class=section-nav-list><li><a href=/documentation/transforms/java/overview/>Overview</a></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Element-wise</span><ul class=section-nav-list><li><a href=/documentation/transforms/java/elementwise/filter/>Filter</a></li><li><a href=/documentation/transforms/java/elementwise/flatmapelements/>FlatMapElements</a></li><li><a href=/documentation/transforms/java/elementwise/keys/>Keys</a></li><li><a href=/documentation/transforms/java/elementwise/kvswap/>KvSwap</a></li><li><a href=/documentation/transforms/java/elementwise/mapelements/>MapElements</a></li><li><a href=/documentation/transforms/java/elementwise/pardo/>ParDo</a></li><li><a href=/documentation/transforms/java/elementwise/partition/>Partition</a></li><li><a href=/documentation/transforms/java/elementwise/regex/>Regex</a></li><li><a href=/documentation/transforms/java/elementwise/reify/>Reify</a></li><li><a href=/documentation/transforms/java/elementwise/tostring/>ToString</a></li><li><a href=/documentation/transforms/java/elementwise/values/>Values</a></li><li><a href=/documentation/transforms/java/elementwise/withkeys/>WithKeys</a></li><li><a href=/documentation/transforms/java/elementwise/withtimestamps/>WithTimestamps</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Aggregation</span><ul class=section-nav-list><li><a href=/documentation/transforms/java/aggregation/approximatequantiles/>ApproximateQuantiles</a></li><li><a href=/documentation/transforms/java/aggregation/approximateunique/>ApproximateUnique</a></li><li><a href=/documentation/transforms/java/aggregation/cogroupbykey/>CoGroupByKey</a></li><li><a href=/documentation/transforms/java/aggregation/combine/>Combine</a></li><li><a href=/documentation/transforms/java/aggregation/combinewithcontext/>CombineWithContext</a></li><li><a href=/documentation/transforms/java/aggregation/count/>Count</a></li><li><a href=/documentation/transforms/java/aggregation/distinct/>Distinct</a></li><li><a href=/documentation/transforms/java/aggregation/groupbykey/>GroupByKey</a></li><li><a href=/documentation/transforms/java/aggregation/groupintobatches/>GroupIntoBatches</a></li><li><a href=/documentation/transforms/java/aggregation/hllcount/>HllCount</a></li><li><a href=/documentation/transforms/java/aggregation/latest/>Latest</a></li><li><a href=/documentation/transforms/java/aggregation/max/>Max</a></li><li><a href=/documentation/transforms/java/aggregation/mean/>Mean</a></li><li><a href=/documentation/transforms/java/aggregation/min/>Min</a></li><li><a href=/documentation/transforms/java/aggregation/sample/>Sample</a></li><li><a href=/documentation/transforms/java/aggregation/sum/>Sum</a></li><li><a href=/documentation/transforms/java/aggregation/top/>Top</a></li></ul></li><li class=section-nav-item--collapsible><span class=section-nav-list-title>Other</span><ul class=section-nav-list><li><a href=/documentation/transforms/java/other/create/>Create</a></li><li><a href=/documentation/transforms/java/other/flatten/>Flatten</a></li><li><a href=/documentation/transforms/java/other/passert/>PAssert</a></li><li><a href=/documentation/transforms/java/other/view/>View</a></li><li><a href=/documentation/transforms/java/other/window/>Window</a></li></ul></li></ul></li></ul></li><li><a href=/documentation/glossary/>Glossary</a></li><li><a href=https://cwiki.apache.org/confluence/display/BEAM/Apache+Beam>Beam Wiki <img src=/images/external-link-icon.png width=14 height=14 alt="External link."></a></li></ul></nav></div><nav class="page-nav clearfix" data-offset-top=90 data-offset-bottom=500><nav id=TableOfContents><ul><li><ul><li><a href=#reading-using-hadoopformatio>Reading using HadoopFormatIO</a><ul><li><a href=#read-data-only-with-hadoop-configuration>Read data only with Hadoop configuration.</a></li><li><a href=#read-data-with-configuration-and-key-translation>Read data with configuration and key translation</a></li><li><a href=#read-data-with-configuration-and-value-translation>Read data with configuration and value translation</a></li><li><a href=#read-data-with-configuration-value-translation-and-key-translation>Read data with configuration, value translation and key translation</a></li></ul></li></ul></li></ul><ul><li><ul><li><a href=#cassandra---cqlinputformat>Cassandra - CqlInputFormat</a></li><li><a href=#elasticsearch---esinputformat>Elasticsearch - EsInputFormat</a></li><li><a href=#hcatalog---hcatinputformat>HCatalog - HCatInputFormat</a></li><li><a href=#amazon-dynamodb---dynamodbinputformat>Amazon DynamoDB - DynamoDBInputFormat</a></li><li><a href=#apache-hbase---tablesnapshotinputformat>Apache HBase - TableSnapshotInputFormat</a></li><li><a href=#writing-using-hadoopformatio>Writing using HadoopFormatIO</a><ul><li><a href=#batch-writing>Batch writing</a></li><li><a href=#stream-writing>Stream writing</a></li></ul></li></ul></li></ul></nav></nav><div class="body__contained body__section-nav arrow-list arrow-list--no-mt"><h1 id=hadoop-inputoutput-format-io>Hadoop Input/Output Format IO</h1><blockquote><p><strong>IMPORTANT!</strong> Previous implementation of Hadoop Input Format IO, called <code>HadoopInputFormatIO</code>, is deprecated starting from <em>Apache Beam 2.10</em>. Please, use current <code>HadoopFormatIO</code> which supports both <code>InputFormat</code> and <code>OutputFormat</code>.</p></blockquote><p>A <code>HadoopFormatIO</code> is a transform for reading data from any source or writing data to any sink that implements Hadoop’s <code>InputFormat</code> or <code>OutputFormat</code> accordingly. For example, Cassandra, Elasticsearch, HBase, Redis, Postgres, etc.</p><p><code>HadoopFormatIO</code> allows you to connect to many data sources/sinks that do not yet have a Beam IO transform. However, <code>HadoopFormatIO</code> has to make several performance trade-offs in connecting to <code>InputFormat</code> or <code>OutputFormat</code>. So, if there is another Beam IO transform for connecting specifically to your data source/sink of choice, we recommend you use that one.</p><h3 id=reading-using-hadoopformatio>Reading using HadoopFormatIO</h3><p>You will need to pass a Hadoop <code>Configuration</code> with parameters specifying how the read will occur. Many properties of the <code>Configuration</code> are optional and some are required for certain <code>InputFormat</code> classes, but the following properties must be set for all <code>InputFormat</code> classes:</p><ul><li><code>mapreduce.job.inputformat.class</code> - The <code>InputFormat</code> class used to connect to your data source of choice.</li><li><code>key.class</code> - The <code>Key</code> class returned by the <code>InputFormat</code> in <code>mapreduce.job.inputformat.class</code>.</li><li><code>value.class</code> - The <code>Value</code> class returned by the <code>InputFormat</code> in <code>mapreduce.job.inputformat.class</code>.</li></ul><p>For example:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>myHadoopConfiguration</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Configuration</span><span class=o>(</span><span class=kc>false</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=c1>// Set Hadoop InputFormat, key and value class in configuration |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.inputformat.class"</span><span class=o>,</span> <span class=n>InputFormatClass</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>InputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"key.class"</span><span class=o>,</span> <span class=n>InputFormatKeyClass</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"value.class"</span><span class=o>,</span> <span class=n>InputFormatValueClass</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>You will need to check if the <code>Key</code> and <code>Value</code> classes output by the <code>InputFormat</code> have a Beam <code>Coder</code> available. If not, you can use <code>withKeyTranslation</code> or <code>withValueTranslation</code> to specify a method transforming instances of those classes into another class that is supported by a Beam <code>Coder</code>. These settings are optional and you don’t need to specify translation for both key and value.</p><p>For example:</p><p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>SimpleFunction</span><span class=o><</span><span class=n>InputFormatKeyClass</span><span class=o>,</span> <span class=n>MyKeyClass</span><span class=o>></span> <span class=n>myOutputKeyType</span> <span class=o>=</span> |
| </span></span><span class=line><span class=cl><span class=k>new</span> <span class=n>SimpleFunction</span><span class=o><</span><span class=n>InputFormatKeyClass</span><span class=o>,</span> <span class=n>MyKeyClass</span><span class=o>>()</span> <span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=kd>public</span> <span class=n>MyKeyClass</span> <span class=nf>apply</span><span class=o>(</span><span class=n>InputFormatKeyClass</span> <span class=n>input</span><span class=o>)</span> <span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=c1>// ...logic to transform InputFormatKeyClass to MyKeyClass |
| </span></span></span><span class=line><span class=cl><span class=c1></span> <span class=o>}</span> |
| </span></span><span class=line><span class=cl><span class=o>};</span> |
| </span></span><span class=line><span class=cl><span class=n>SimpleFunction</span><span class=o><</span><span class=n>InputFormatValueClass</span><span class=o>,</span> <span class=n>MyValueClass</span><span class=o>></span> <span class=n>myOutputValueType</span> <span class=o>=</span> |
| </span></span><span class=line><span class=cl><span class=k>new</span> <span class=n>SimpleFunction</span><span class=o><</span><span class=n>InputFormatValueClass</span><span class=o>,</span> <span class=n>MyValueClass</span><span class=o>>()</span> <span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=kd>public</span> <span class=n>MyValueClass</span> <span class=nf>apply</span><span class=o>(</span><span class=n>InputFormatValueClass</span> <span class=n>input</span><span class=o>)</span> <span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=c1>// ...logic to transform InputFormatValueClass to MyValueClass |
| </span></span></span><span class=line><span class=cl><span class=c1></span> <span class=o>}</span> |
| </span></span><span class=line><span class=cl><span class=o>};</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div></p><h4 id=read-data-only-with-hadoop-configuration>Read data only with Hadoop configuration.</h4><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>InputFormatKeyClass</span><span class=o>,</span> <span class=n>InputFormatKeyClass</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>myHadoopConfiguration</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h4 id=read-data-with-configuration-and-key-translation>Read data with configuration and key translation</h4><p>For example, a Beam <code>Coder</code> is not available for <code>Key</code> class, so key translation is required.</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>MyKeyClass</span><span class=o>,</span> <span class=n>InputFormatKeyClass</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>myHadoopConfiguration</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withKeyTranslation</span><span class=o>(</span><span class=n>myOutputKeyType</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h4 id=read-data-with-configuration-and-value-translation>Read data with configuration and value translation</h4><p>For example, a Beam <code>Coder</code> is not available for <code>Value</code> class, so value translation is required.</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>InputFormatKeyClass</span><span class=o>,</span> <span class=n>MyValueClass</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>myHadoopConfiguration</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withValueTranslation</span><span class=o>(</span><span class=n>myOutputValueType</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h4 id=read-data-with-configuration-value-translation-and-key-translation>Read data with configuration, value translation and key translation</h4><p>For example, Beam Coders are not available for both <code>Key</code> class and <code>Value</code> classes of <code>InputFormat</code>, so key and value translation are required.</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>MyKeyClass</span><span class=o>,</span> <span class=n>MyValueClass</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>myHadoopConfiguration</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withKeyTranslation</span><span class=o>(</span><span class=n>myOutputKeyType</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withValueTranslation</span><span class=o>(</span><span class=n>myOutputValueType</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h1 id=examples-for-specific-inputformats>Examples for specific InputFormats</h1><h3 id=cassandra---cqlinputformat>Cassandra - CqlInputFormat</h3><p>To read data from Cassandra, use <code>org.apache.cassandra.hadoop.cql3.CqlInputFormat</code>, which needs the following properties to be set:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>cassandraConf</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Configuration</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"cassandra.input.thrift.port"</span><span class=o>,</span> <span class=s>"9160"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"cassandra.input.thrift.address"</span><span class=o>,</span> <span class=n>CassandraHostIp</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"cassandra.input.partitioner.class"</span><span class=o>,</span> <span class=s>"Murmur3Partitioner"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"cassandra.input.keyspace"</span><span class=o>,</span> <span class=s>"myKeySpace"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"cassandra.input.columnfamily"</span><span class=o>,</span> <span class=s>"myColumnFamily"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"key.class"</span><span class=o>,</span> <span class=n>java</span><span class=o>.</span><span class=na>lang</span><span class=o>.</span><span class=na>Long</span> <span class=n>Long</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"value.class"</span><span class=o>,</span> <span class=n>com</span><span class=o>.</span><span class=na>datastax</span><span class=o>.</span><span class=na>driver</span><span class=o>.</span><span class=na>core</span><span class=o>.</span><span class=na>Row</span> <span class=n>Row</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>cassandraConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.inputformat.class"</span><span class=o>,</span> <span class=n>org</span><span class=o>.</span><span class=na>apache</span><span class=o>.</span><span class=na>cassandra</span><span class=o>.</span><span class=na>hadoop</span><span class=o>.</span><span class=na>cql3</span><span class=o>.</span><span class=na>CqlInputFormat</span> <span class=n>CqlInputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>InputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>Call Read transform as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>PCollection</span><span class=o><</span><span class=n>KV</span><span class=o><</span><span class=n>Long</span><span class=o>,</span> <span class=n>String</span><span class=o>>></span> <span class=n>cassandraData</span> <span class=o>=</span> |
| </span></span><span class=line><span class=cl> <span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>Long</span><span class=o>,</span> <span class=n>String</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>cassandraConf</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withValueTranslation</span><span class=o>(</span><span class=n>cassandraOutputValueType</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>The <code>CqlInputFormat</code> key class is <code>java.lang.Long</code> <code>Long</code>, which has a Beam <code>Coder</code>. The <code>CqlInputFormat</code> value class is <code>com.datastax.driver.core.Row</code> <code>Row</code>, which does not have a Beam <code>Coder</code>. Rather than write a new coder, you can provide your own translation method, as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>SimpleFunction</span><span class=o><</span><span class=n>Row</span><span class=o>,</span> <span class=n>String</span><span class=o>></span> <span class=n>cassandraOutputValueType</span> <span class=o>=</span> <span class=n>SimpleFunction</span><span class=o><</span><span class=n>Row</span><span class=o>,</span> <span class=n>String</span><span class=o>>()</span> |
| </span></span><span class=line><span class=cl><span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=kd>public</span> <span class=n>String</span> <span class=nf>apply</span><span class=o>(</span><span class=n>Row</span> <span class=n>row</span><span class=o>)</span> <span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=k>return</span> <span class=n>row</span><span class=o>.</span><span class=na>getString</span><span class=o>(</span><span class=err>'</span><span class=n>myColName</span><span class=err>'</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl> <span class=o>}</span> |
| </span></span><span class=line><span class=cl><span class=o>};</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h3 id=elasticsearch---esinputformat>Elasticsearch - EsInputFormat</h3><p>To read data from Elasticsearch, use <code>EsInputFormat</code>, which needs following properties to be set:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>elasticsearchConf</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Configuration</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>elasticsearchConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"es.nodes"</span><span class=o>,</span> <span class=n>ElasticsearchHostIp</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>elasticsearchConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"es.port"</span><span class=o>,</span> <span class=s>"9200"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>elasticsearchConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"es.resource"</span><span class=o>,</span> <span class=s>"ElasticIndexName/ElasticTypeName"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>elasticsearchConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"key.class"</span><span class=o>,</span> <span class=n>org</span><span class=o>.</span><span class=na>apache</span><span class=o>.</span><span class=na>hadoop</span><span class=o>.</span><span class=na>io</span><span class=o>.</span><span class=na>Text</span> <span class=n>Text</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>elasticsearchConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"value.class"</span><span class=o>,</span> <span class=n>org</span><span class=o>.</span><span class=na>elasticsearch</span><span class=o>.</span><span class=na>hadoop</span><span class=o>.</span><span class=na>mr</span><span class=o>.</span><span class=na>LinkedMapWritable</span> <span class=n>LinkedMapWritable</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>elasticsearchConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.inputformat.class"</span><span class=o>,</span> <span class=n>org</span><span class=o>.</span><span class=na>elasticsearch</span><span class=o>.</span><span class=na>hadoop</span><span class=o>.</span><span class=na>mr</span><span class=o>.</span><span class=na>EsInputFormat</span> <span class=n>EsInputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>InputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>Call Read transform as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>PCollection</span><span class=o><</span><span class=n>KV</span><span class=o><</span><span class=n>Text</span><span class=o>,</span> <span class=n>LinkedMapWritable</span><span class=o>>></span> <span class=n>elasticData</span> <span class=o>=</span> <span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>Text</span><span class=o>,</span> <span class=n>LinkedMapWritable</span><span class=o>></span><span class=n>read</span><span class=o>().</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>elasticsearchConf</span><span class=o>));</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>The <code>org.elasticsearch.hadoop.mr.EsInputFormat</code>’s <code>EsInputFormat</code> key class is <code>org.apache.hadoop.io.Text</code> <code>Text</code>, and its value class is <code>org.elasticsearch.hadoop.mr.LinkedMapWritable</code> <code>LinkedMapWritable</code>. Both key and value classes have Beam Coders.</p><h3 id=hcatalog---hcatinputformat>HCatalog - HCatInputFormat</h3><p>To read data using HCatalog, use <code>org.apache.hive.hcatalog.mapreduce.HCatInputFormat</code>, which needs the following properties to be set:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>hcatConf</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Configuration</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>hcatConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.inputformat.class"</span><span class=o>,</span> <span class=n>HCatInputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>InputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hcatConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"key.class"</span><span class=o>,</span> <span class=n>LongWritable</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hcatConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"value.class"</span><span class=o>,</span> <span class=n>HCatRecord</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hcatConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"hive.metastore.uris"</span><span class=o>,</span> <span class=s>"thrift://metastore-host:port"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=n>org</span><span class=o>.</span><span class=na>apache</span><span class=o>.</span><span class=na>hive</span><span class=o>.</span><span class=na>hcatalog</span><span class=o>.</span><span class=na>mapreduce</span><span class=o>.</span><span class=na>HCatInputFormat</span><span class=o>.</span><span class=na>setInput</span><span class=o>(</span><span class=n>hcatConf</span><span class=o>,</span> <span class=s>"my_database"</span><span class=o>,</span> <span class=s>"my_table"</span><span class=o>,</span> <span class=s>"my_filter"</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>Call Read transform as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>PCollection</span><span class=o><</span><span class=n>KV</span><span class=o><</span><span class=n>Long</span><span class=o>,</span> <span class=n>HCatRecord</span><span class=o>>></span> <span class=n>hcatData</span> <span class=o>=</span> |
| </span></span><span class=line><span class=cl> <span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>Long</span><span class=o>,</span> <span class=n>HCatRecord</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>hcatConf</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h3 id=amazon-dynamodb---dynamodbinputformat>Amazon DynamoDB - DynamoDBInputFormat</h3><p>To read data from Amazon DynamoDB, use <code>org.apache.hadoop.dynamodb.read.DynamoDBInputFormat</code>. |
| DynamoDBInputFormat implements the older <code>org.apache.hadoop.mapred.InputFormat</code> interface and to make it compatible with HadoopFormatIO which uses the newer abstract class <code>org.apache.hadoop.mapreduce.InputFormat</code>, |
| a wrapper API is required which acts as an adapter between HadoopFormatIO and DynamoDBInputFormat (or in general any InputFormat implementing <code>org.apache.hadoop.mapred.InputFormat</code>) |
| The below example uses one such available wrapper API - <a href=https://github.com/twitter/elephant-bird/blob/master/core/src/main/java/com/twitter/elephantbird/mapreduce/input/MapReduceInputFormatWrapper.java>https://github.com/twitter/elephant-bird/blob/master/core/src/main/java/com/twitter/elephantbird/mapreduce/input/MapReduceInputFormatWrapper.java</a></p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>dynamoDBConf</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Configuration</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>Job</span> <span class=n>job</span> <span class=o>=</span> <span class=n>Job</span><span class=o>.</span><span class=na>getInstance</span><span class=o>(</span><span class=n>dynamoDBConf</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>com</span><span class=o>.</span><span class=na>twitter</span><span class=o>.</span><span class=na>elephantbird</span><span class=o>.</span><span class=na>mapreduce</span><span class=o>.</span><span class=na>input</span><span class=o>.</span><span class=na>MapReduceInputFormatWrapper</span><span class=o>.</span><span class=na>setInputFormat</span><span class=o>(</span><span class=n>org</span><span class=o>.</span><span class=na>apache</span><span class=o>.</span><span class=na>hadoop</span><span class=o>.</span><span class=na>dynamodb</span><span class=o>.</span><span class=na>read</span><span class=o>.</span><span class=na>DynamoDBInputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>job</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span> <span class=o>=</span> <span class=n>job</span><span class=o>.</span><span class=na>getConfiguration</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"key.class"</span><span class=o>,</span> <span class=n>Text</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>WritableComparable</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"value.class"</span><span class=o>,</span> <span class=n>org</span><span class=o>.</span><span class=na>apache</span><span class=o>.</span><span class=na>hadoop</span><span class=o>.</span><span class=na>dynamodb</span><span class=o>.</span><span class=na>DynamoDBItemWritable</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Writable</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.servicename"</span><span class=o>,</span> <span class=s>"dynamodb"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.input.tableName"</span><span class=o>,</span> <span class=s>"table_name"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.endpoint"</span><span class=o>,</span> <span class=s>"dynamodb.us-west-1.amazonaws.com"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.regionid"</span><span class=o>,</span> <span class=s>"us-west-1"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.throughput.read"</span><span class=o>,</span> <span class=s>"1"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.throughput.read.percent"</span><span class=o>,</span> <span class=s>"1"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"dynamodb.version"</span><span class=o>,</span> <span class=s>"2011-12-05"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=n>DynamoDBConstants</span><span class=o>.</span><span class=na>DYNAMODB_ACCESS_KEY_CONF</span><span class=o>,</span> <span class=s>"aws_access_key"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>dynamoDBConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=n>DynamoDBConstants</span><span class=o>.</span><span class=na>DYNAMODB_SECRET_KEY_CONF</span><span class=o>,</span> <span class=s>"aws_secret_key"</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>Call Read transform as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>PCollection</span><span class=o><</span><span class=n>Text</span><span class=o>,</span> <span class=n>DynamoDBItemWritable</span><span class=o>></span> <span class=n>dynamoDBData</span> <span class=o>=</span> |
| </span></span><span class=line><span class=cl> <span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>Text</span><span class=o>,</span> <span class=n>DynamoDBItemWritable</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>dynamoDBConf</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h3 id=apache-hbase---tablesnapshotinputformat>Apache HBase - TableSnapshotInputFormat</h3><p>To read data from an HBase table snapshot, use <code>org.apache.hadoop.hbase.mapreduce.TableSnapshotInputFormat</code>. |
| Reading from a table snapshot bypasses the HBase region servers, instead reading HBase data files directly from the filesystem. |
| This is useful for cases such as reading historical data or offloading of work from the HBase cluster. |
| There are scenarios when this may prove faster than accessing content through the region servers using the <code>HBaseIO</code>.</p><p>A table snapshot can be taken using the HBase shell or programmatically:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=k>try</span> <span class=o>(</span> |
| </span></span><span class=line><span class=cl> <span class=n>Connection</span> <span class=n>connection</span> <span class=o>=</span> <span class=n>ConnectionFactory</span><span class=o>.</span><span class=na>createConnection</span><span class=o>(</span><span class=n>hbaseConf</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl> <span class=n>Admin</span> <span class=n>admin</span> <span class=o>=</span> <span class=n>connection</span><span class=o>.</span><span class=na>getAdmin</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>)</span> <span class=o>{</span> |
| </span></span><span class=line><span class=cl> <span class=n>admin</span><span class=o>.</span><span class=na>snapshot</span><span class=o>(</span> |
| </span></span><span class=line><span class=cl> <span class=s>"my_snaphshot"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>TableName</span><span class=o>.</span><span class=na>valueOf</span><span class=o>(</span><span class=s>"my_table"</span><span class=o>),</span> |
| </span></span><span class=line><span class=cl> <span class=n>HBaseProtos</span><span class=o>.</span><span class=na>SnapshotDescription</span><span class=o>.</span><span class=na>Type</span><span class=o>.</span><span class=na>FLUSH</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=o>}</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>A <code>TableSnapshotInputFormat</code> is configured as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=c1>// Construct a typical HBase scan |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>Scan</span> <span class=n>scan</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Scan</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>scan</span><span class=o>.</span><span class=na>setCaching</span><span class=o>(</span><span class=n>1000</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>scan</span><span class=o>.</span><span class=na>setBatch</span><span class=o>(</span><span class=n>1000</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>scan</span><span class=o>.</span><span class=na>addColumn</span><span class=o>(</span><span class=n>Bytes</span><span class=o>.</span><span class=na>toBytes</span><span class=o>(</span><span class=s>"CF"</span><span class=o>),</span> <span class=n>Bytes</span><span class=o>.</span><span class=na>toBytes</span><span class=o>(</span><span class=s>"col_1"</span><span class=o>));</span> |
| </span></span><span class=line><span class=cl><span class=n>scan</span><span class=o>.</span><span class=na>addColumn</span><span class=o>(</span><span class=n>Bytes</span><span class=o>.</span><span class=na>toBytes</span><span class=o>(</span><span class=s>"CF"</span><span class=o>),</span> <span class=n>Bytes</span><span class=o>.</span><span class=na>toBytes</span><span class=o>(</span><span class=s>"col_2"</span><span class=o>));</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>hbaseConf</span> <span class=o>=</span> <span class=n>HBaseConfiguration</span><span class=o>.</span><span class=na>create</span><span class=o>();</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=n>HConstants</span><span class=o>.</span><span class=na>ZOOKEEPER_QUORUM</span><span class=o>,</span> <span class=s>"zk1:2181"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=s>"hbase.rootdir"</span><span class=o>,</span> <span class=s>"/hbase"</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span> |
| </span></span><span class=line><span class=cl> <span class=s>"mapreduce.job.inputformat.class"</span><span class=o>,</span> <span class=n>TableSnapshotInputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>InputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"key.class"</span><span class=o>,</span> <span class=n>ImmutableBytesWritable</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Writable</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"value.class"</span><span class=o>,</span> <span class=n>Result</span><span class=o>.</span><span class=na>class</span><span class=o>,</span> <span class=n>Writable</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>ClientProtos</span><span class=o>.</span><span class=na>Scan</span> <span class=n>proto</span> <span class=o>=</span> <span class=n>ProtobufUtil</span><span class=o>.</span><span class=na>toScan</span><span class=o>(</span><span class=n>scan</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span><span class=o>.</span><span class=na>set</span><span class=o>(</span><span class=n>TableInputFormat</span><span class=o>.</span><span class=na>SCAN</span><span class=o>,</span> <span class=n>Base64</span><span class=o>.</span><span class=na>encodeBytes</span><span class=o>(</span><span class=n>proto</span><span class=o>.</span><span class=na>toByteArray</span><span class=o>()));</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=c1>// Make use of existing utility methods |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>Job</span> <span class=n>job</span> <span class=o>=</span> <span class=n>Job</span><span class=o>.</span><span class=na>getInstance</span><span class=o>(</span><span class=n>hbaseConf</span><span class=o>);</span> <span class=c1>// creates internal clone of hbaseConf |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>TableSnapshotInputFormat</span><span class=o>.</span><span class=na>setInput</span><span class=o>(</span><span class=n>job</span><span class=o>,</span> <span class=s>"my_snapshot"</span><span class=o>,</span> <span class=k>new</span> <span class=n>Path</span><span class=o>(</span><span class=s>"/tmp/snapshot_restore"</span><span class=o>));</span> |
| </span></span><span class=line><span class=cl><span class=n>hbaseConf</span> <span class=o>=</span> <span class=n>job</span><span class=o>.</span><span class=na>getConfiguration</span><span class=o>();</span> <span class=c1>// extract the modified clone |
| </span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>Call Read transform as follows:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>PCollection</span><span class=o><</span><span class=n>ImmutableBytesWritable</span><span class=o>,</span> <span class=n>Result</span><span class=o>></span> <span class=n>hbaseSnapshotData</span> <span class=o>=</span> |
| </span></span><span class=line><span class=cl> <span class=n>p</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span><span class=s>"read"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>ImmutableBytesWritable</span><span class=o>,</span> <span class=n>Result</span><span class=o>></span><span class=n>read</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>hbaseConf</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h3 id=writing-using-hadoopformatio>Writing using HadoopFormatIO</h3><p>You will need to pass a Hadoop <code>Configuration</code> with parameters specifying how the write will occur. Many properties of the <code>Configuration</code> are optional, and some are required for certain <code>OutputFormat</code> classes, but the following properties must be set for all <code>OutputFormat</code>s:</p><ul><li><code>mapreduce.job.id</code> - The identifier of the write job. E.g.: end timestamp of window.</li><li><code>mapreduce.job.outputformat.class</code> - The <code>OutputFormat</code> class used to connect to your data sink of choice.</li><li><code>mapreduce.job.output.key.class</code> - The key class passed to the <code>OutputFormat</code> in <code>mapreduce.job.outputformat.class</code>.</li><li><code>mapreduce.job.output.value.class</code> - The value class passed to the <code>OutputFormat</code> in <code>mapreduce.job.outputformat.class</code>.</li><li><code>mapreduce.job.reduces</code> - Number of reduce tasks. Value is equal to number of write tasks which will be generated. This property is not required for <code>Write.PartitionedWriterBuilder#withoutPartitioning()</code> write.</li><li><code>mapreduce.job.partitioner.class</code> - Hadoop partitioner class which will be used for distributing of records among partitions. This property is not required for <code>Write.PartitionedWriterBuilder#withoutPartitioning()</code> write.</li></ul><p><em>Note</em>: All mentioned values have appropriate constants. E.g.: <code>HadoopFormatIO.OUTPUT_FORMAT_CLASS_ATTR</code>.</p><p>For example:</p><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=n>Configuration</span> <span class=n>myHadoopConfiguration</span> <span class=o>=</span> <span class=k>new</span> <span class=n>Configuration</span><span class=o>(</span><span class=kc>false</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=c1>// Set Hadoop OutputFormat, key and value class in configuration |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.outputformat.class"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>MyDbOutputFormatClass</span><span class=o>,</span> <span class=n>OutputFormat</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.output.key.class"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>MyDbOutputFormatKeyClass</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.output.value.class"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>MyDbOutputFormatValueClass</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setClass</span><span class=o>(</span><span class=s>"mapreduce.job.partitioner.class"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>MyPartitionerClass</span><span class=o>,</span> <span class=n>Object</span><span class=o>.</span><span class=na>class</span><span class=o>);</span> |
| </span></span><span class=line><span class=cl><span class=n>myHadoopConfiguration</span><span class=o>.</span><span class=na>setInt</span><span class=o>(</span><span class=s>"mapreduce.job.reduces"</span><span class=o>,</span> <span class=n>2</span><span class=o>);</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><p>You will need to set <code>OutputFormat</code> key and value class (i.e. “mapreduce.job.output.key.class” and “mapreduce.job.output.value.class”) in Hadoop <code>Configuration</code> which are equal to <code>KeyT</code> and <code>ValueT</code>. If you set different <code>OutputFormat</code> key or value class than <code>OutputFormat</code>’s actual key or value class then, it will throw <code>IllegalArgumentException</code>.</p><h4 id=batch-writing>Batch writing</h4><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=c1>// Data which will we want to write |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>PCollection</span><span class=o><</span><span class=n>KV</span><span class=o><</span><span class=n>Text</span><span class=o>,</span> <span class=n>LongWritable</span><span class=o>>></span> <span class=n>boundedWordsCount</span> <span class=o>=</span> <span class=o>...</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=c1>// Hadoop configuration for write |
| </span></span></span><span class=line><span class=cl><span class=c1>// We have partitioned write, so Partitioner and reducers count have to be set - see withPartitioning() javadoc |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>Configuration</span> <span class=n>myHadoopConfiguration</span> <span class=o>=</span> <span class=o>...</span> |
| </span></span><span class=line><span class=cl><span class=c1>// Path to directory with locks |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>String</span> <span class=n>locksDirPath</span> <span class=o>=</span> <span class=o>...;</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=n>boundedWordsCount</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span> |
| </span></span><span class=line><span class=cl> <span class=s>"writeBatch"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>Text</span><span class=o>,</span> <span class=n>LongWritable</span><span class=o>></span><span class=n>write</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfiguration</span><span class=o>(</span><span class=n>myHadoopConfiguration</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withPartitioning</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withExternalSynchronization</span><span class=o>(</span><span class=k>new</span> <span class=n>HDFSSynchronization</span><span class=o>(</span><span class=n>locksDirPath</span><span class=o>)));</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><h4 id=stream-writing>Stream writing</h4><div class='language-java snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-java data-lang=java><span class=line><span class=cl><span class=c1>// Data which will we want to write |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>PCollection</span><span class=o><</span><span class=n>KV</span><span class=o><</span><span class=n>Text</span><span class=o>,</span> <span class=n>LongWritable</span><span class=o>>></span> <span class=n>unboundedWordsCount</span> <span class=o>=</span> <span class=o>...;</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=c1>// Transformation which transforms data of one window into one hadoop configuration |
| </span></span></span><span class=line><span class=cl><span class=c1></span><span class=n>PTransform</span><span class=o><</span><span class=n>PCollection</span><span class=o><?</span> <span class=kd>extends</span> <span class=n>KV</span><span class=o><</span><span class=n>Text</span><span class=o>,</span> <span class=n>LongWritable</span><span class=o>>>,</span> <span class=n>PCollectionView</span><span class=o><</span><span class=n>Configuration</span><span class=o>>></span> |
| </span></span><span class=line><span class=cl> <span class=n>configTransform</span> <span class=o>=</span> <span class=o>...;</span> |
| </span></span><span class=line><span class=cl> |
| </span></span><span class=line><span class=cl><span class=n>unboundedWordsCount</span><span class=o>.</span><span class=na>apply</span><span class=o>(</span> |
| </span></span><span class=line><span class=cl> <span class=s>"writeStream"</span><span class=o>,</span> |
| </span></span><span class=line><span class=cl> <span class=n>HadoopFormatIO</span><span class=o>.<</span><span class=n>Text</span><span class=o>,</span> <span class=n>LongWritable</span><span class=o>></span><span class=n>write</span><span class=o>()</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withConfigurationTransform</span><span class=o>(</span><span class=n>configTransform</span><span class=o>)</span> |
| </span></span><span class=line><span class=cl> <span class=o>.</span><span class=na>withExternalSynchronization</span><span class=o>(</span><span class=k>new</span> <span class=n>HDFSSynchronization</span><span class=o>(</span><span class=n>locksDirPath</span><span class=o>)));</span></span></span></code></pre></div></div></div><div class='language-py snippet'><div class="notebook-skip code-snippet"><a class=copy type=button data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img src=/images/copy-icon.svg></a><div class=highlight><pre tabindex=0 class=chroma><code class=language-py data-lang=py><span class=line><span class=cl> <span class=c1># The Beam SDK for Python does not support Hadoop Input/Output Format IO.</span></span></span></code></pre></div></div></div><div class=feedback><p class=update>Last updated on 2024/05/11</p><h3>Have you found everything you were looking for?</h3><p class=description>Was it all useful and clear? Is there anything that you would like to change? Let us know!</p><button class=load-button><a href="https://docs.google.com/forms/d/e/1FAIpQLSfID7abne3GE6k6RdJIyZhPz2Gef7UkpggUEhTIDjjplHuxSA/viewform?usp=header_link" target=_blank>SEND FEEDBACK</a></button></div></div></div><footer class=footer><div class=footer__contained><div class=footer__cols><div class="footer__cols__col footer__cols__col__logos"><div class=footer__cols__col__logo><img src=/images/beam_logo_circle.svg class=footer__logo alt="Beam logo"></div><div class=footer__cols__col__logo><img src=/images/apache_logo_circle.svg class=footer__logo alt="Apache logo"></div></div><div class=footer-wrapper><div class=wrapper-grid><div class=footer__cols__col><div class=footer__cols__col__title>Start</div><div class=footer__cols__col__link><a href=/get-started/beam-overview/>Overview</a></div><div class=footer__cols__col__link><a href=/get-started/quickstart-java/>Quickstart (Java)</a></div><div class=footer__cols__col__link><a href=/get-started/quickstart-py/>Quickstart (Python)</a></div><div class=footer__cols__col__link><a href=/get-started/quickstart-go/>Quickstart (Go)</a></div><div class=footer__cols__col__link><a href=/get-started/downloads/>Downloads</a></div></div><div class=footer__cols__col><div class=footer__cols__col__title>Docs</div><div class=footer__cols__col__link><a href=/documentation/programming-guide/>Concepts</a></div><div class=footer__cols__col__link><a href=/documentation/pipelines/design-your-pipeline/>Pipelines</a></div><div class=footer__cols__col__link><a href=/documentation/runners/capability-matrix/>Runners</a></div></div><div class=footer__cols__col><div class=footer__cols__col__title>Community</div><div class=footer__cols__col__link><a href=/contribute/>Contribute</a></div><div class=footer__cols__col__link><a href=https://projects.apache.org/committee.html?beam target=_blank>Team<img src=/images/external-link-icon.png width=14 height=14 alt="External link."></a></div><div class=footer__cols__col__link><a href=/community/presentation-materials/>Media</a></div><div class=footer__cols__col__link><a href=/community/in-person/>Events/Meetups</a></div><div class=footer__cols__col__link><a href=/community/contact-us/>Contact Us</a></div></div><div class=footer__cols__col><div class=footer__cols__col__title>Resources</div><div class=footer__cols__col__link><a href=/blog/>Blog</a></div><div class=footer__cols__col__link><a href=https://github.com/apache/beam>GitHub</a></div></div></div><div class=footer__bottom>© |
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