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class="menu__link header-linkedin-link" aria-label="Hudi Linkedin Page"><div class="labelWrapperDropdown_Mqbj"></div></a></li></ul></div><div class="navbar-sidebar__item menu"><button type="button" class="clean-btn navbar-sidebar__back">← Back to main menu</button></div></div></div></nav><div class="main-wrapper docs-wrapper docs-doc-page"><div class="docPage_GMj9"><button aria-label="Scroll back to top" class="clean-btn theme-back-to-top-button backToTopButton_i9tI" type="button"></button><main class="docMainContainer_Q970 docMainContainerEnhanced_ipQ4"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_zHA2"><div class="theme-doc-version-banner alert alert--warning margin-bottom--md" role="alert"><div>This is documentation for <!-- -->Apache Hudi<!-- --> <b>0.6.0</b>, which is no longer actively maintained.</div><div class="margin-top--md">For up-to-date documentation, see the <b><a href="/cn/docs/migration_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: <!-- -->0.6.0</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>Migration Guide</h1></header><p>Hudi maintains metadata such as commit timeline and indexes to manage a dataset. The commit timelines helps to understand the actions happening on a dataset as well as the current state of a dataset. Indexes are used by Hudi to maintain a record key to file id mapping to efficiently locate a record. At the moment, Hudi supports writing only parquet columnar formats. |
| To be able to start using Hudi for your existing dataset, you will need to migrate your existing dataset into a Hudi managed dataset. There are a couple of ways to achieve this.</p><h2 class="anchor anchorWithStickyNavbar_y2LR" id="approaches">Approaches<a class="hash-link" href="#approaches" title="Direct link to heading"></a></h2><h3 class="anchor anchorWithStickyNavbar_y2LR" id="use-hudi-for-new-partitions-alone">Use Hudi for new partitions alone<a class="hash-link" href="#use-hudi-for-new-partitions-alone" title="Direct link to heading"></a></h3><p>Hudi can be used to manage an existing dataset without affecting/altering the historical data already present in the |
| dataset. Hudi has been implemented to be compatible with such a mixed dataset with a caveat that either the complete |
| Hive partition is Hudi managed or not. Thus the lowest granularity at which Hudi manages a dataset is a Hive |
| partition. Start using the datasource API or the WriteClient to write to the dataset and make sure you start writing |
| to a new partition or convert your last N partitions into Hudi instead of the entire table. Note, since the historical |
| partitions are not managed by HUDI, none of the primitives provided by HUDI work on the data in those partitions. More concretely, one cannot perform upserts or incremental pull on such older partitions not managed by the HUDI dataset. |
| Take this approach if your dataset is an append only type of dataset and you do not expect to perform any updates to existing (or non Hudi managed) partitions.</p><h3 class="anchor anchorWithStickyNavbar_y2LR" id="convert-existing-dataset-to-hudi">Convert existing dataset to Hudi<a class="hash-link" href="#convert-existing-dataset-to-hudi" title="Direct link to heading"></a></h3><p>Import your existing dataset into a Hudi managed dataset. Since all the data is Hudi managed, none of the limitations |
| of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently |
| make the update available to queries. Note that not only do you get to use all Hudi primitives on this dataset, |
| there are other additional advantages of doing this. Hudi automatically manages file sizes of a Hudi managed dataset |
| . You can define the desired file size when converting this dataset and Hudi will ensure it writes out files |
| adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into |
| small files rather than writing new small ones thus maintaining the health of your cluster.</p><p>There are a few options when choosing this approach.</p><p><strong>Option 1</strong> |
| Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in parquet file format. |
| This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.</p><p><strong>Option 2</strong> |
| For huge datasets, this could be as simple as : </p><div class="codeBlockContainer_J+bg language-java theme-code-block"><div class="codeBlockContent_csEI java"><pre tabindex="0" class="prism-code language-java 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">for partition in [list of partitions in source dataset] {</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> val inputDF = spark.read.format("any_input_format").load("partition_path")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> inputDF.write.format("org.apache.hudi").option()....save("basePath")</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain">}</span><br></span></code></pre><button type="button" aria-label="Copy code to clipboard" class="copyButton_M3SB clean-btn">Copy</button></div></div><p><strong>Option 3</strong> |
| Write your own custom logic of how to load an existing dataset into a Hudi managed one. Please read about the RDD API |
| <a href="/cn/docs/quick-start-guide">here</a>. Using the HDFSParquetImporter Tool. Once hudi has been built via <code>mvn clean install -DskipTests</code>, the shell can be |
| fired by via <code>cd hudi-cli && ./hudi-cli.sh</code>.</p><div class="codeBlockContainer_J+bg language-java theme-code-block"><div class="codeBlockContent_csEI java"><pre tabindex="0" class="prism-code language-java 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">hudi->hdfsparquetimport</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --upsert false</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --srcPath /user/parquet/dataset/basepath</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --targetPath</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> /user/hoodie/dataset/basepath</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --tableName hoodie_table</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --tableType COPY_ON_WRITE</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --rowKeyField _row_key</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --partitionPathField partitionStr</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --parallelism 1500</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --schemaFilePath /user/table/schema</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --format parquet</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --sparkMemory 6g</span><br></span><span class="token-line" style="color:#F8F8F2"><span class="token plain"> --retry 2</span><br></span></code></pre><button type="button" aria-label="Copy code to 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