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</a><div class="searchBox_ZlJk"><button type="button" class="DocSearch DocSearch-Button" aria-label="Search"><span class="DocSearch-Button-Container"><svg width="20" height="20" class="DocSearch-Search-Icon" viewBox="0 0 20 20" aria-hidden="true"><path d="M14.386 14.386l4.0877 4.0877-4.0877-4.0877c-2.9418 2.9419-7.7115 2.9419-10.6533 0-2.9419-2.9418-2.9419-7.7115 0-10.6533 2.9418-2.9419 7.7115-2.9419 10.6533 0 2.9419 2.9418 2.9419 7.7115 0 10.6533z" stroke="currentColor" fill="none" fill-rule="evenodd" stroke-linecap="round" stroke-linejoin="round"></path></svg><span class="DocSearch-Button-Placeholder">Search</span></span><span class="DocSearch-Button-Keys"></span></button></div></div></div><div role="presentation" class="navbar-sidebar__backdrop"></div></nav><div id="__docusaurus_skipToContent_fallback" class="main-wrapper mainWrapper_z2l0 docsWrapper_BCFX"><button aria-label="Scroll back to top" class="clean-btn theme-back-to-top-button backToTopButton_sjWU" type="button"></button><div class="docPage__5DB"><aside class="theme-doc-sidebar-container docSidebarContainer_b6E3"><div class="sidebarViewport_Xe31"><div class="sidebar_njMd"><nav aria-label="Docs sidebar" class="menu thin-scrollbar menu_SIkG menuWithAnnouncementBar_GW3s"><ul class="theme-doc-sidebar-menu menu__list"><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-1 menuHtmlItem_M9Kj menu__list-item"><div>Getting Started</div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist" aria-expanded="false" href="/docs/features">What Is DataHub?</a><button aria-label="Toggle the collapsible sidebar category 'What Is DataHub?'" type="button" class="clean-btn menu__caret"></button></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist" aria-expanded="false" href="/docs/category/features">Features</a><button aria-label="Toggle the collapsible sidebar category 'Features'" type="button" class="clean-btn menu__caret"></button></div></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-1 menuHtmlItem_M9Kj menu__list-item"><div>DataHub Cloud</div></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-1 menu__list-item"><a class="menu__link" href="/docs/managed-datahub/managed-datahub-overview">DataHub Cloud Overview</a></li><li class="theme-doc-sidebar-item-link theme-doc-sidebar-item-link-level-1 menu__list-item"><a class="menu__link" href="/docs/managed-datahub/welcome-acryl">Getting Started with DataHub Cloud</a></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" aria-expanded="false" href="/docs/authentication/guides/sso/initialize-oidc">Configure Single Sign-On</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" aria-expanded="false" href="/docs/managed-datahub/remote-executor/about">Remote Executor</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--sublist-caret" aria-expanded="false" href="/docs/managed-datahub/datahub-api/entity-events-api">DataHub API</a></div></li><li class="theme-doc-sidebar-item-category theme-doc-sidebar-item-category-level-1 menu__list-item menu__list-item--collapsed"><div class="menu__list-item-collapsible"><a class="menu__link menu__link--sublist menu__link--subli
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Refer to the section <a href="/docs/generated/ingestion/sources/s3/#path-specs">Path Specs</a> for more details.</p><div class="theme-admonition theme-admonition-tip alert alert--success admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 12 16"><path fill-rule="evenodd" d="M6.5 0C3.48 0 1 2.19 1 5c0 .92.55 2.25 1 3 1.34 2.25 1.78 2.78 2 4v1h5v-1c.22-1.22.66-1.75 2-4 .45-.75 1-2.08 1-3 0-2.81-2.48-5-5.5-5zm3.64 7.48c-.25.44-.47.8-.67 1.11-.86 1.41-1.25 2.06-1.45 3.23-.02.05-.02.11-.02.17H5c0-.06 0-.13-.02-.17-.2-1.17-.59-1.83-1.45-3.23-.2-.31-.42-.67-.67-1.11C2.44 6.78 2 5.65 2 5c0-2.2 2.02-4 4.5-4 1.22 0 2.36.42 3.22 1.19C10.55 2.94 11 3.94 11 5c0 .66-.44 1.78-.86 2.48zM4 14h5c-.23 1.14-1.3 2-2.5 2s-2.27-.86-2.5-2z"></path></svg></span>tip</div><div class="admonitionContent_S0QG"><p>This connector can also be used to ingest local files.
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Just replace <code>s3://</code> in your path_specs with an absolute path to files on the machine running ingestion.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="supported-file-types">Supported file types<a href="#supported-file-types" class="hash-link" aria-label="Direct link to Supported file types" title="Direct link to Supported file types"></a></h3><p>Supported file types are as follows:</p><ul><li>CSV (<!-- -->*<!-- -->.csv)</li><li>TSV (<!-- -->*<!-- -->.tsv)</li><li>JSONL (<!-- -->*<!-- -->.jsonl)</li><li>JSON (<!-- -->*<!-- -->.json)</li><li>Parquet (<!-- -->*<!-- -->.parquet)</li><li>Apache Avro (<!-- -->*<!-- -->.avro)</li></ul><p>Schemas for Parquet and Avro files are extracted as provided.</p><p>Schemas for schemaless formats (CSV, TSV, JSONL, JSON) are inferred. For CSV, TSV and JSONL files, we consider the first 100 rows by default, which can be controlled via the <code>max_rows</code> recipe parameter (see <a href="#config-details">below</a>)
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JSON file schemas are inferred on the basis of the entire file (given the difficulty in extracting only the first few objects of the file), which may impact performance.
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We are working on using iterator-based JSON parsers to avoid reading in the entire JSON object.</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="concept-mapping">Concept Mapping<a href="#concept-mapping" class="hash-link" aria-label="Direct link to Concept Mapping" title="Direct link to Concept Mapping"></a></h3><p>This ingestion source maps the following Source System Concepts to DataHub Concepts:</p><table><thead><tr><th>Source Concept</th><th>DataHub Concept</th><th>Notes</th></tr></thead><tbody><tr><td><code>"s3"</code></td><td><a href="/docs/generated/metamodel/entities/dataplatform/">Data Platform</a></td><td></td></tr><tr><td>s3 object / Folder containing s3 objects</td><td><a href="/docs/generated/metamodel/entities/dataset/">Dataset</a></td><td></td></tr><tr><td>s3 bucket</td><td><a href="/docs/generated/metamodel/entities/container/">Container</a></td><td>Subtype <code>S3 bucket</code></td></tr><tr><td>s3 folder</td><td><a href="/docs/generated/metamodel/entities/container/">Container</a></td><td>Subtype <code>Folder</code></td></tr></tbody></table><h3 class="anchor anchorWithStickyNavbar_LWe7" id="profiling">Profiling<a href="#profiling" class="hash-link" aria-label="Direct link to Profiling" title="Direct link to Profiling"></a></h3><p>This plugin extracts:</p><ul><li>Row and column counts for each dataset</li><li>For each column, if profiling is enabled:<ul><li>null counts and proportions</li><li>distinct counts and proportions</li><li>minimum, maximum, mean, median, standard deviation, some quantile values</li><li>histograms or frequencies of unique values</li></ul></li></ul><p>Note that because the profiling is run with PySpark, we require Spark 3.0.3 with Hadoop 3.2 to be installed (see <a href="#compatibility">compatibility</a> for more details). If profiling, make sure that permissions for <strong>s3a://</strong> access are set because Spark and Hadoop use the s3a:// protocol to interface with AWS (schema inference outside of profiling requires s3:// access).
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Enabling profiling will slow down ingestion runs.
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<img loading="lazy" src="https://img.shields.io/badge/support%20status-incubating-blue" alt="Incubating" class="img_ev3q"></p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="important-capabilities">Important Capabilities<a href="#important-capabilities" class="hash-link" aria-label="Direct link to Important Capabilities" title="Direct link to Important Capabilities"></a></h3><table><thead><tr><th>Capability</th><th>Status</th><th>Notes</th></tr></thead><tbody><tr><td>Asset Containers</td><td>✅</td><td>Enabled by default.</td></tr><tr><td><a href="/docs/metadata-ingestion/docs/dev_guides/sql_profiles">Data Profiling</a></td><td>✅</td><td>Optionally enabled via configuration.</td></tr><tr><td><a href="/docs/metadata-ingestion/docs/dev_guides/stateful#stale-entity-removal">Detect Deleted Entities</a></td><td>✅</td><td>Enabled by default via stateful ingestion.</td></tr><tr><td>Extract Tags</td><td>✅</td><td>Can extract S3 object/bucket tags if enabled.</td></tr><tr><td>Schema Metadata</td><td>✅</td><td>Can infer schema from supported file types.</td></tr></tbody></table><h3 class="anchor anchorWithStickyNavbar_LWe7" id="prerequisites">Prerequisites<a href="#prerequisites" class="hash-link" aria-label="Direct link to Prerequisites" title="Direct link to Prerequisites"></a></h3><p>To allow the S3 ingestion source ingest metadata from an S3 bucket, you need to grant the necessary permissions to an IAM user or role. Follow these steps:</p><ol><li><strong>Create an IAM Policy</strong>: Create a policy that grants read access to the S3 bucket.</li></ol><div class="language-json codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-json codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token punctuation" style="color:rgb(199, 146, 234)">{</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token property">"Version"</span><span class="token operator" style="color:rgb(137, 221, 255)">:</span><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">"2012-10-17"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token property">"Statement"</span><span class="token operator" style="color:rgb(137, 221, 255)">:</span><span class="token plain"> </span><span class="token punctuation" style="color:rgb(199, 146, 234)">[</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token punctuation" style="color:rgb(199, 146, 234)">{</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token property">"Sid"</span><span class="token operator" style="color:rgb(137, 221, 255)">:</span><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">"VisualEditor0"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token property">"Effect"</span><span class="token operator" style="color:rgb(137, 221, 255)">:</span><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">"Allow"</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> </span><span class="token property">"Action"</span><span class="token
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3 if the path is in the form of /value1/value2/value3 the source infer partition value from the path and assign partition_0, partition_1, partition_2 etc</li></ol><p>Dataset creation time is determined by the creation time of earliest created file in the lowest partition while last updated time is determined by the last updated time of the latest updated file in the highest partition.</p><p>How the source determines the highest/lowest partition it is based on the traversal method set in the path_spec.</p><ul><li>If the traversal method is set to <code>MAX</code> then the source will try to find the latest partition by ordering the partitions each level and find the latest partiton. This traversal method won't look for earilest partition/creation time but this is the fastest.</li><li>If the traversal method is set to <code>MIN_MAX</code> then the source will try to find the latest and earliest partition by ordering the partitions each level and find the latest/earliest partiton. This traversal sort folders purely by name therefor it is fast but it doesn't guarantee the latest partition will have the latest created file.</li><li>If the traversal method is set to <code>ALL</code> then the source will try to find the latest and earliest partition by listing all the files in all the partitions and find the creation/last modification time based on the file creations. This is the slowest but for non time partitioned datasets this is the only way to find the latest/earliest partition.</li></ul><h3 class="anchor anchorWithStickyNavbar_LWe7" id="path-specs---examples">Path Specs - Examples<a href="#path-specs---examples" class="hash-link" aria-label="Direct link to Path Specs - Examples" title="Direct link to Path Specs - Examples"></a></h3><h4 class="anchor anchorWithStickyNavbar_LWe7" id="example-1---individual-file-as-dataset">Example 1 - Individual file as Dataset<a href="#example-1---individual-file-as-dataset" class="hash-link" aria-label="Direct link to Example 1 - Individual file as Dataset" title="Direct link to Example 1 - Individual file as Dataset"></a></h4><p>Bucket structure:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token plain">test-bucket</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">├── employees.csv</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">├── departments.json</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">└── food_items.csv</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>Path specs config to ingest <code>employees.csv</code> and <code>food_items.csv</code> as datasets:</p><div class="codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-text codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token plain">path_specs:</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"> - include: s3://test-bucket/*.csv</span><br></span><span class="token-line" style="color:#bfc7
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and will ignore file <code>tmp_10101000.csv</code></li></ul><p><strong>Valid path_specs.include</strong></p><div class="language-python codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-python codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token plain">s3</span><span class="token punctuation" style="color:rgb(199, 146, 234)">:</span><span class="token operator" style="color:rgb(137, 221, 255)">//</span><span class="token plain">my</span><span class="token operator" style="color:rgb(137, 221, 255)">-</span><span class="token plain">bucket</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">foo</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">tests</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">bar</span><span class="token punctuation" style="color:rgb(199, 146, 234)">.</span><span class="token plain">avro </span><span class="token comment" style="color:rgb(105, 112, 152);font-style:italic"># single file table</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">s3</span><span class="token punctuation" style="color:rgb(199, 146, 234)">:</span><span class="token operator" style="color:rgb(137, 221, 255)">//</span><span class="token plain">my</span><span class="token operator" style="color:rgb(137, 221, 255)">-</span><span class="token plain">bucket</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">foo</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">tests</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token operator" style="color:rgb(137, 221, 255)">*</span><span class="token punctuation" style="color:rgb(199, 146, 234)">.</span><span class="token operator" style="color:rgb(137, 221, 255)">*</span><span class="token plain"> </span><span class="token comment" style="color:rgb(105, 112, 152);font-style:italic"># mulitple file level tables</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">s3</span><span class="token punctuation" style="color:rgb(199, 146, 234)">:</span><span class="token operator" style="color:rgb(137, 221, 255)">//</span><span class="token plain">my</span><span class="token operator" style="color:rgb(137, 221, 255)">-</span><span class="token plain">bucket</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">foo</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token plain">tests</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token punctuation" style="color:rgb(199, 146, 234)">{</span><span class="token plain">table</span><span class="token punctuation" style="color:rgb(199, 146, 234)">}</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span class="token operator" style="color:rgb(137, 221, 255)">*</span><span class="token punctuation" style="color:rgb(199, 146, 234)">.</span><span class="token plain">avro </span><span class="token comment" style="color:rgb(105, 112, 152);font-style:italic">#table without partition</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">s3</span><span class="token punctuation" style="color:rgb(199, 146, 234)">:</span><span class="token operator" style="color:rgb(137, 221, 255)">//</span><span class="token plain">my</span><span class="token operator" style="color:rgb(137, 221, 255)">-</span><span class="token plain">bucket</span><span class="token operator" style="color:rgb(137, 221, 255)">/</span><span clas
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While we've done our best to limit the expensiveness of the queries the profiler runs, you
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should be prudent about the set of tables profiling is enabled on or the frequency
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of the profiling runs.</p></div></div><div class="theme-admonition theme-admonition-caution alert alert--warning admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>caution</div><div class="admonitionContent_S0QG"><p>If you are ingesting datasets from AWS S3, we recommend running the ingestion on a server in the same region to avoid high egress costs.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="compatibility">Compatibility<a href="#compatibility" class="hash-link" aria-label="Direct link to Compatibility" title="Direct link to Compatibility"></a></h3><p>Profiles are computed with PyDeequ, which relies on PySpark. Therefore, for computing profiles, we currently require Spark 3.0.3 with Hadoop 3.2 to be installed and the <code>SPARK_HOME</code> and <code>SPARK_VERSION</code> environment variables to be set. The Spark+Hadoop binary can be downloaded <a href="https://www.apache.org/dyn/closer.lua/spark/spark-3.0.3/spark-3.0.3-bin-hadoop3.2.tgz" target="_blank" rel="noopener noreferrer">here</a>.</p><p>For an example guide on setting up PyDeequ on AWS, see <a href="https://aws.amazon.com/blogs/big-data/testing-data-quality-at-scale-with-pydeequ/" target="_blank" rel="noopener noreferrer">this guide</a>.</p><div class="theme-admonition theme-admonition-caution alert alert--warning admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>caution</div><div class="admonitionContent_S0QG"><p>From Spark 3.2.0+, Avro reader fails on column names that don't start with a letter and contains other character than letters, number, and underscore. <!-- -->[https://github.com/apache/spark/blob/72c62b6596d21e975c5597f8fff84b1a9d070a02/connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroFileFormat.scala#L158]<!-- -->
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Avro files that contain such columns won't be profiled.</p></div></div><h3 class="anchor anchorWithStickyNavbar_LWe7" id="code-coordinates">Code Coordinates<a href="#code-coordinates" class="hash-link" aria-label="Direct link to Code Coordinates" title="Direct link to Code Coordinates"></a></h3><ul><li>Class Name: <code>datahub.ingestion.source.s3.source.S3Source</code></li><li>Browse on <a href="https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/src/datahub/ingestion/source/s3/source.py" target="_blank" rel="noopener noreferrer">GitHub</a></li></ul><h2>Questions</h2><p>If you've got any questions on configuring ingestion for S3 / Local Files, feel free to ping us on <a href="https://datahub.com/slack" target="_blank" rel="noopener noreferrer">our Slack</a>.</p></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="slackUtm_uoBr"><div class="slackUtm_uoBr"><hr>Need more help? Join the conversation in <a href="https://datahub.com/slack?utm_source=docs&utm_medium=footer&utm_campaign=docs_footer&utm_content=docs/generated/ingestion/sources/s3">Slack!</a></div></div><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/datahub-project/datahub/blob/master/docs/generated/ingestion/sources/s3.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_Z9Sw" 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_VsjB"></div></div></footer><div class="feedbackWrapper_mUHF"><div class="feedbackWidget_PX4d"><div class="feedbackButtons_wn3V"><strong>Is this page helpful?</strong><div><button class="feedbackButton_UgQs"><span role="img" aria-label="like" class="anticon anticon-like"><svg viewBox="64 64 896 896" focusable="false" data-icon="like" width="1em" height="1em" fill="currentColor" aria-hidden="true"><path d="M885.9 533.7c16.8-22.2 26.1-49.4 26.1-77.7 0-44.9-25.1-87.4-65.5-111.1a67.67 67.67 0 00-34.3-9.3H572.4l6-122.9c1.4-29.7-9.1-57.9-29.5-79.4A106.62 106.62 0 00471 99.9c-52 0-98 35-111.8 85.1l-85.9 311H144c-17.7 0-32 14.3-32 32v364c0 17.7 14.3 32 32 32h601.3c9.2 0 18.2-1.8 26.5-5.4 47.6-20.3 78.3-66.8 78.3-118.4 0-12.6-1.8-25-5.4-37 16.8-22.2 26.1-49.4 26.1-77.7 0-12.6-1.8-25-5.4-37 16.8-22.2 26.1-49.4 26.1-77.7-.2-12.6-2-25.1-5.6-37.1zM184 852V568h81v284h-81zm636.4-353l-21.9 19 13.9 25.4a56.2 56.2 0 016.9 27.3c0 16.5-7.2 32.2-19.6 43l-21.9 19 13.9 25.4a56.2 56.2 0 016.9 27.3c0 16.5-7.2 32.2-19.6 43l-21.9 19 13.9 25.4a56.2 56.2 0 016.9 27.3c0 22.4-13.2 42.6-33.6 51.8H329V564.8l99.5-360.5a44.1 44.1 0 0142.2-32.3c7.6 0 15.1 2.2 21.1 6.7 9.9 7.4 15.2 18.6 14.6 30.5l-9.6 198.4h314.4C829 418.5 840 436.9 840 456c0 16.5-7.2 32.1-19.6 43z"></path></svg></span></button><button class="feedbackButton_UgQs"><span role="img" aria-label="dislike" class="anticon anticon-dislike"><svg viewBox="64 64 896 896" focusable="false" data-icon="dislike" width="1em" height="1em" fill="currentColor" aria-hidden="true"><path d="M885.9 490.3c3.6-12 5.4-24.4 5.4-37 0-28.3-9.3-55.5-26.1-77.7 3.6-12 5.4-24.4 5.4-37 0-28.3-9.3-55.5-26.1-77.7 3.6-12 5.4-24.4 5.4-37 0-51.6-30.7-98.1-78.3-118.4a66.1 66.1 0 00-26.5-5.4H144c-17.7 0-32 14.3-32 32v364c0 17.7 14.3 32 32 32h129.3l85.8 310.8C372.9 889 418.9 924 470.9 924c29.7 0 57.4-11.8 77.9-33.4 20.5-21.5 31-49.7 29.5-79.4l-6-122.9h239.9c12.1 0 23.9-3.2 34.3-9.3 40.4-23.5 65.5-66.1 65.5-111 0-28.3-9.3-55.5-26.1-77.7zM184 456V172h81v284h-81zm627.2 160.4H496.8l9.6 198.4c.6 11.9-4.7 23.1-14.6 30.5-6.1 4.5-13.6 6.8-21.1 6.7a44.28 44.28 0 01-42.2-32.3L329 459.2V172h415.4a56.85 56.85 0 0133.6 51.8c0 9.7-2.3 18.9-6.9 27.3l-13.9 25.4 21.9 19a56.76 56.76 0 0119.6 43c0 9.7-2.3 18.9-6.9 27.3l-13.9 25.4 21.9 19a56.76 56.76 0 0119.6 43c0 9.7-2.3 18.9-6.9 27.3l-14 25.5 21.9 19a56.76 56.76 0 0119.6 43c0 19.1-11 37.5-28.8 48.4z"></path></svg></span>
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