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-->Apache Hudi<!-- --> <b>0.5.1</b>, which is no longer actively maintained.</div><div class="margin-top--md">For up-to-date documentation, see the <b><a href="/docs/quick-start-guide">latest version</a></b> (<!-- -->0.14.1<!-- -->).</div></div><div class="docItemContainer_oiyr"><article><span class="theme-doc-version-badge badge badge--secondary">Version: <!-- -->0.5.1</span><div class="tocCollapsible_aw-L theme-doc-toc-mobile tocMobile_Tx6Y"><button type="button" class="clean-btn tocCollapsibleButton_zr6a">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Quick-Start Guide</h1></header><p>This guide provides a quick peek at Hudi's capabilities using spark-shell. Using Spark datasources, we will walk through |
| code snippets that allows you to insert and update a Hudi table of default table type: |
| <a href="/docs/concepts#copy-on-write-table">Copy on Write</a>. |
| After each write operation we will also show how to read the data both snapshot and incrementally.</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="setup-spark-shell">Setup spark-shell<a class="hash-link" href="#setup-spark-shell" title="Direct link to heading"></a></h2><p>Hudi works with Spark-2.x versions. You can follow instructions <a href="https://spark.apache.org/downloads" target="_blank" rel="noopener noreferrer">here</a> for setting up spark. |
| From the extracted directory run spark-shell with Hudi as:</p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark-2.4.4-bin-hadoop2.7/bin/spark-shell \</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --packages org.apache.hudi:hudi-spark-bundle_2.11:0.5.1-incubating,org.apache.spark:spark-avro_2.11:2.4.4 \</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer'</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><div class="notice--info"><h4>Please note the following: </h4><ul><li>spark-avro module needs to be specified in --packages as it is not included with spark-shell by default</li><li>spark-avro and spark versions must match (we have used 2.4.4 for both above)</li><li>we have used hudi-spark-bundle built for scala 2.11 since the spark-avro module used also depends on 2.11. If spark-avro_2.12 is used, correspondingly hudi-spark-bundle_2.12 needs to be used. </li></ul></div><p>Setup table name, base path and a data generator to generate records for this guide.</p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.hudi.QuickstartUtils._</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import scala.collection.JavaConversions._</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.spark.sql.SaveMode._</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.hudi.DataSourceReadOptions._</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.hudi.DataSourceWriteOptions._</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">import org.apache.hudi.config.HoodieWriteConfig._</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block"></span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val tableName = "hudi_trips_cow"</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val basePath = "file:///tmp/hudi_trips_cow"</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val dataGen = new DataGenerator</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p>The <a href="https://github.com/apache/hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L50" target="_blank" rel="noopener noreferrer">DataGenerator</a> |
| can generate sample inserts and updates based on the the sample trip schema <a href="https://github.com/apache/hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L57" target="_blank" rel="noopener noreferrer">here</a> |
| {: .notice--info}</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="insert-data">Insert data<a class="hash-link" href="#insert-data" title="Direct link to heading"></a></h2><p>Generate some new trips, load them into a DataFrame and write the DataFrame into the Hudi table as below.</p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">val inserts = convertToStringList(dataGen.generateInserts(10))</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val df = spark.read.json(spark.sparkContext.parallelize(inserts, 2))</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">df.write.format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> options(getQuickstartWriteConfigs).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(PRECOMBINE_FIELD_OPT_KEY, "ts").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(RECORDKEY_FIELD_OPT_KEY, "uuid").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(TABLE_NAME, tableName).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> mode(Overwrite).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> save(basePath);</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p><code>mode(Overwrite)</code> overwrites and recreates the table if it already exists. |
| You can check the data generated under <code>/tmp/hudi_trips_cow/<region>/<country>/<city>/</code>. We provided a record key |
| (<code>uuid</code> in <a href="https://github.com/apache/hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L58" target="_blank" rel="noopener noreferrer">schema</a>), partition field (<code>region/county/city</code>) and combine logic (<code>ts</code> in |
| <a href="https://github.com/apache/hudi/blob/master/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java#L58" target="_blank" rel="noopener noreferrer">schema</a>) to ensure trip records are unique within each partition. For more info, refer to |
| <a href="https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=113709185#FAQ-HowdoImodelthedatastoredinHudi" target="_blank" rel="noopener noreferrer">Modeling data stored in Hudi</a> |
| and for info on ways to ingest data into Hudi, refer to <a href="/docs/writing_data">Writing Hudi Tables</a>. |
| Here we are using the default write operation : <code>upsert</code>. If you have a workload without updates, you can also issue |
| <code>insert</code> or <code>bulk_insert</code> operations which could be faster. To know more, refer to <a href="/docs/writing_data#write-operations">Write operations</a> |
| {: .notice--info}</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="query-data">Query data<a class="hash-link" href="#query-data" title="Direct link to heading"></a></h2><p>Load the data files into a DataFrame.</p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">val tripsSnapshotDF = spark.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> read.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> load(basePath + "/*/*/*/*")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">tripsSnapshotDF.createOrReplaceTempView("hudi_trips_snapshot")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.sql("select fare, begin_lon, begin_lat, ts from hudi_trips_snapshot where fare > 20.0").show()</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.sql("select _hoodie_commit_time, _hoodie_record_key, _hoodie_partition_path, rider, driver, fare from hudi_trips_snapshot").show()</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p>This query provides snapshot querying of the ingested data. Since our partition path (<code>region/country/city</code>) is 3 levels nested |
| from base path we ve used <code>load(basePath + "/*/*/*/*")</code>. |
| Refer to <a href="/docs/concepts#table-types--queries">Table types and queries</a> for more info on all table types and query types supported. |
| {: .notice--info}</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="update-data">Update data<a class="hash-link" href="#update-data" title="Direct link to heading"></a></h2><p>This is similar to inserting new data. Generate updates to existing trips using the data generator, load into a DataFrame |
| and write DataFrame into the hudi table.</p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">val updates = convertToStringList(dataGen.generateUpdates(10))</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val df = spark.read.json(spark.sparkContext.parallelize(updates, 2));</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">df.write.format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> options(getQuickstartWriteConfigs).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(PRECOMBINE_FIELD_OPT_KEY, "ts").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(RECORDKEY_FIELD_OPT_KEY, "uuid").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(TABLE_NAME, tableName).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> mode(Append).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> save(basePath);</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p>Notice that the save mode is now <code>Append</code>. In general, always use append mode unless you are trying to create the table for the first time. |
| <a href="#query-data">Querying</a> the data again will now show updated trips. Each write operation generates a new <a href="http://hudi.incubator.apache.org/docs/concepts" target="_blank" rel="noopener noreferrer">commit</a> |
| denoted by the timestamp. Look for changes in <code>_hoodie_commit_time</code>, <code>rider</code>, <code>driver</code> fields for the same <code>_hoodie_record_key</code>s in previous commit. |
| {: .notice--info}</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="incremental-query">Incremental query<a class="hash-link" href="#incremental-query" title="Direct link to heading"></a></h2><p>Hudi also provides capability to obtain a stream of records that changed since given commit timestamp. |
| This can be achieved using Hudi's incremental querying and providing a begin time from which changes need to be streamed. |
| We do not need to specify endTime, if we want all changes after the given commit (as is the common case). </p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">// reload data</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> read.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> load(basePath + "/*/*/*/*").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> createOrReplaceTempView("hudi_trips_snapshot")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block"></span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val commits = spark.sql("select distinct(_hoodie_commit_time) as commitTime from hudi_trips_snapshot order by commitTime").map(k => k.getString(0)).take(50)</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val beginTime = commits(commits.length - 2) // commit time we are interested in</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block"></span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">// incrementally query data</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val tripsIncrementalDF = spark.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> read.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(BEGIN_INSTANTTIME_OPT_KEY, beginTime).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> load(basePath);</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">tripsIncrementalDF.createOrReplaceTempView("hudi_trips_incremental")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.sql("select `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts from hudi_trips_incremental where fare > 20.0").show()</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p>This will give all changes that happened after the beginTime commit with the filter of fare > 20.0. The unique thing about this |
| feature is that it now lets you author streaming pipelines on batch data. |
| {: .notice--info}</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="point-in-time-query">Point in time query<a class="hash-link" href="#point-in-time-query" title="Direct link to heading"></a></h2><p>Lets look at how to query data as of a specific time. The specific time can be represented by pointing endTime to a |
| specific commit time and beginTime to "000" (denoting earliest possible commit time). </p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">val beginTime = "000" // Represents all commits > this time.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val endTime = commits(commits.length - 2) // commit time we are interested in</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block"></span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">//incrementally query data</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val tripsPointInTimeDF = spark.read.format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(BEGIN_INSTANTTIME_OPT_KEY, beginTime).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> option(END_INSTANTTIME_OPT_KEY, endTime).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> load(basePath);</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">tripsPointInTimeDF.createOrReplaceTempView("hudi_trips_point_in_time")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.sql("select `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts from hudi_trips_point_in_time where fare > 20.0").show()</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><h2 class="anchor anchorWithStickyNavbar_y2LR" id="deletes">Delete data<a class="hash-link" href="#deletes" title="Direct link to heading"></a></h2><p>Delete records for the HoodieKeys passed in.</p><div class="codeBlockContainer_J+bg language-scala theme-code-block"><div class="codeBlockContent_csEI scala"><pre tabindex="0" class="prism-code language-scala codeBlock_rtdJ thin-scrollbar" style="color:#F8F8F2;background-color:#282A36"><code class="codeBlockLines_1zSZ"><span class="token-line" style="color:#F8F8F2"><span class="token plain">// fetch total records count</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.sql("select uuid, partitionPath from hudi_ro_table").count()</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">// fetch two records to be deleted</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val ds = spark.sql("select uuid, partitionPath from hudi_ro_table").limit(2)</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block"></span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">// issue deletes</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val deletes = dataGen.generateDeletes(ds.collectAsList())</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val df = spark.read.json(spark.sparkContext.parallelize(deletes, 2));</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">df.write.format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">options(getQuickstartWriteConfigs).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">option(OPERATION_OPT_KEY,"delete").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">option(PRECOMBINE_FIELD_OPT_KEY, "ts").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">option(RECORDKEY_FIELD_OPT_KEY, "uuid").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">option(TABLE_NAME, tableName).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">mode(Append).</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">save(basePath);</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain" style="display:inline-block"></span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">// run the same read query as above.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">val roAfterDeleteViewDF = spark.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> read.</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> format("org.apache.hudi").</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> load(basePath + "/*/*/*/*")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">roAfterDeleteViewDF.registerTempTable("hudi_ro_table")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">// fetch should return (total - 2) records</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">spark.sql("select uuid, partitionPath from hudi_ro_table").count()</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p>Note: Only <code>Append</code> mode is supported for delete operation.</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="where-to-go-from-here">Where to go from here?<a class="hash-link" href="#where-to-go-from-here" title="Direct link to heading"></a></h2><p>You can also do the quickstart by <a href="https://github.com/apache/hudi#building-apache-hudi-from-source" target="_blank" rel="noopener noreferrer">building hudi yourself</a>, |
| and using <code>--jars <path to hudi_code>/packaging/hudi-spark-bundle/target/hudi-spark-bundle_2.11-*.*.*-SNAPSHOT.jar</code> in the spark-shell command above |
| instead of <code>--packages org.apache.hudi:hudi-spark-bundle_2.11:0.5.1-incubating</code>. Hudi also supports scala 2.12. Refer <a href="https://github.com/apache/hudi#build-with-scala-212" target="_blank" rel="noopener noreferrer">build with scala 2.12</a> |
| for more info.</p><p>Also, we used Spark here to show case the capabilities of Hudi. However, Hudi can support multiple table types/query types and |
| Hudi tables can be queried from query engines like Hive, Spark, Presto and much more. We have put together a |
| <a href="https://www.youtube.com/watch?v=VhNgUsxdrD0" target="_blank" rel="noopener noreferrer">demo video</a> that show cases all of this on a docker based setup with all |
| dependent systems running locally. We recommend you replicate the same setup and run the demo yourself, by following |
| steps <a href="/docs/docker_demo">here</a> to get a taste for it. Also, if you are looking for ways to migrate your existing data |
| to Hudi, refer to <a href="/docs/migration_guide">migration guide</a>.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/apache/hudi/tree/asf-site/website/versioned_docs/version-0.5.1/quick-start-guide.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_mS5F" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_mt2f"></div></div></footer></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages navigation"><div class="pagination-nav__item"></div><div class="pagination-nav__item pagination-nav__item--next"><a class="pagination-nav__link" href="/docs/0.5.1/use_cases"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Use Cases</div></a></div></nav></div></div><div class="col col--3"><div class="tableOfContents_vrFS thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#setup-spark-shell" class="table-of-contents__link toc-highlight">Setup spark-shell</a></li><li><a href="#insert-data" class="table-of-contents__link toc-highlight">Insert data</a></li><li><a href="#query-data" class="table-of-contents__link toc-highlight">Query data</a></li><li><a href="#update-data" class="table-of-contents__link toc-highlight">Update data</a></li><li><a href="#incremental-query" class="table-of-contents__link toc-highlight">Incremental query</a></li><li><a href="#point-in-time-query" class="table-of-contents__link toc-highlight">Point in time query</a></li><li><a href="#deletes" class="table-of-contents__link toc-highlight">Delete data</a></li><li><a href="#where-to-go-from-here" 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