<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Catch rejected Data ( Rows ) while reading with Apache-Spark. in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34946#M25639</link>
    <description>&lt;P&gt;maybe &lt;A href="https://docs.microsoft.com/en-us/azure/databricks/data-engineering/delta-live-tables/delta-live-tables-user-guide#--expectations" alt="https://docs.microsoft.com/en-us/azure/databricks/data-engineering/delta-live-tables/delta-live-tables-user-guide#--expectations" target="_blank"&gt;Delta Live tables&lt;/A&gt;?&lt;/P&gt;&lt;P&gt;Not sure if it is what you are looking for, haven't used it myself.  But you have schema evolution and expectations so it might bring you there.&lt;/P&gt;</description>
    <pubDate>Tue, 16 Nov 2021 18:51:06 GMT</pubDate>
    <dc:creator>-werners-</dc:creator>
    <dc:date>2021-11-16T18:51:06Z</dc:date>
    <item>
      <title>Catch rejected Data ( Rows ) while reading with Apache-Spark.</title>
      <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34942#M25635</link>
      <description>&lt;P&gt;I work with Spark-Scala and I receive Data in different formats ( .csv/.xlxs/.txt etc ), when I try to read/write this data from different sources to a any database, many records got rejected due to various issues like (special characters, data type difference between source and target table etc. In such cases, my entire load gets failed.&lt;/P&gt;&lt;P&gt;what I want is a way to capture the rejected rows into separate file and continue to load remaining correct records in database table.&lt;/P&gt;&lt;P&gt;basically not to stop the flow of the program due to some rows, and catch these problem causing rows.&lt;/P&gt;&lt;P&gt;example -&lt;/P&gt;&lt;P&gt;I read a .csv with 98 perfect rows and 2 corrupt rows, I want to read/write 98 rows into the database and send 2 corrupt rows to the user as a file.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;P.S. I am receiving data from user so i can't define a schema, i need a dynamic way to read the file and filter out the corrupt data in a file.&lt;/P&gt;</description>
      <pubDate>Tue, 16 Nov 2021 17:36:51 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34942#M25635</guid>
      <dc:creator>sarvesh</dc:creator>
      <dc:date>2021-11-16T17:36:51Z</dc:date>
    </item>
    <item>
      <title>Re: Catch rejected Data ( Rows ) while reading with Apache-Spark.</title>
      <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34943#M25636</link>
      <description>&lt;P&gt;you can save corrupted records to separate file:&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;.option("badRecordsPath", "/tmp/badRecordsPath")&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;allow spark to process corrupted row:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;.option("mode", "PERMISSIVE")&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;you can also create special column for corrupted records:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;df = spark.read.csv('/tmp/inputFile.csv', header=True, schema=dataSchema, enforceSchema=True, 
&amp;nbsp;
columnNameOfCorruptRecord='CORRUPTED')&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 16 Nov 2021 18:01:14 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34943#M25636</guid>
      <dc:creator>Hubert-Dudek</dc:creator>
      <dc:date>2021-11-16T18:01:14Z</dc:date>
    </item>
    <item>
      <title>Re: Catch rejected Data ( Rows ) while reading with Apache-Spark.</title>
      <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34944#M25637</link>
      <description>&lt;P&gt;Thank you for replying, but what I am trying to develop is a function that can take data from user and filter out corrupt records if any, that is I want to do the same thing you did but without a defined Schema.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Tue, 16 Nov 2021 18:47:21 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34944#M25637</guid>
      <dc:creator>sarvesh</dc:creator>
      <dc:date>2021-11-16T18:47:21Z</dc:date>
    </item>
    <item>
      <title>Re: Catch rejected Data ( Rows ) while reading with Apache-Spark.</title>
      <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34945#M25638</link>
      <description>&lt;P&gt;I might get data from some external source and i can't define a schema for the data which is read on my website/app.&lt;/P&gt;</description>
      <pubDate>Tue, 16 Nov 2021 18:48:37 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34945#M25638</guid>
      <dc:creator>sarvesh</dc:creator>
      <dc:date>2021-11-16T18:48:37Z</dc:date>
    </item>
    <item>
      <title>Re: Catch rejected Data ( Rows ) while reading with Apache-Spark.</title>
      <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34946#M25639</link>
      <description>&lt;P&gt;maybe &lt;A href="https://docs.microsoft.com/en-us/azure/databricks/data-engineering/delta-live-tables/delta-live-tables-user-guide#--expectations" alt="https://docs.microsoft.com/en-us/azure/databricks/data-engineering/delta-live-tables/delta-live-tables-user-guide#--expectations" target="_blank"&gt;Delta Live tables&lt;/A&gt;?&lt;/P&gt;&lt;P&gt;Not sure if it is what you are looking for, haven't used it myself.  But you have schema evolution and expectations so it might bring you there.&lt;/P&gt;</description>
      <pubDate>Tue, 16 Nov 2021 18:51:06 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34946#M25639</guid>
      <dc:creator>-werners-</dc:creator>
      <dc:date>2021-11-16T18:51:06Z</dc:date>
    </item>
    <item>
      <title>Re: Catch rejected Data ( Rows ) while reading with Apache-Spark.</title>
      <link>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34947#M25640</link>
      <description>&lt;P&gt;or maybe schema evolution on delta lake is enough, in combination with Hubert's answer&lt;/P&gt;</description>
      <pubDate>Tue, 16 Nov 2021 19:00:19 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/catch-rejected-data-rows-while-reading-with-apache-spark/m-p/34947#M25640</guid>
      <dc:creator>-werners-</dc:creator>
      <dc:date>2021-11-16T19:00:19Z</dc:date>
    </item>
  </channel>
</rss>

