<?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: sharikrishna26.medium.com in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14076#M8628</link>
    <description>&lt;P&gt;good post thanks&lt;/P&gt;</description>
    <pubDate>Sun, 01 Jan 2023 08:09:52 GMT</pubDate>
    <dc:creator>Aviral-Bhardwaj</dc:creator>
    <dc:date>2023-01-01T08:09:52Z</dc:date>
    <item>
      <title>sharikrishna26.medium.com</title>
      <link>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14074#M8626</link>
      <description>&lt;P&gt;&lt;B&gt;Spark Dataframes Schema&lt;/B&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;B&gt;Schema inference is not reliable.&lt;/B&gt;&lt;/P&gt;&lt;P&gt;We have the following problems in schema inference:&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;Automatic inferring of schema is often incorrect&lt;/LI&gt;&lt;LI&gt;Inferring schema is additional work for Spark, and it takes some extra time&lt;/LI&gt;&lt;LI&gt;Schema inference is conflicting with the schema validation&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;4. It might also change the column order&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;We have two approaches to do it.&lt;/P&gt;&lt;OL&gt;&lt;LI&gt;Schema DDL String&lt;/LI&gt;&lt;LI&gt;Struct Type Object&lt;/LI&gt;&lt;/OL&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Further Detailed description please refer this link&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://sharikrishna26.medium.com/spark-dataframes-schema-6fe1f90a56c" target="test_blank"&gt;https://sharikrishna26.medium.com/spark-dataframes-schema-6fe1f90a56c&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Please like,share,comment&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Happy New year 2023&lt;/P&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 31 Dec 2022 13:38:45 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14074#M8626</guid>
      <dc:creator>SIRIGIRI</dc:creator>
      <dc:date>2022-12-31T13:38:45Z</dc:date>
    </item>
    <item>
      <title>Re: sharikrishna26.medium.com</title>
      <link>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14075#M8627</link>
      <description>&lt;P&gt;Thanks for sharing &lt;/P&gt;</description>
      <pubDate>Sat, 31 Dec 2022 16:26:30 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14075#M8627</guid>
      <dc:creator>Rishabh-Pandey</dc:creator>
      <dc:date>2022-12-31T16:26:30Z</dc:date>
    </item>
    <item>
      <title>Re: sharikrishna26.medium.com</title>
      <link>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14076#M8628</link>
      <description>&lt;P&gt;good post thanks&lt;/P&gt;</description>
      <pubDate>Sun, 01 Jan 2023 08:09:52 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14076#M8628</guid>
      <dc:creator>Aviral-Bhardwaj</dc:creator>
      <dc:date>2023-01-01T08:09:52Z</dc:date>
    </item>
    <item>
      <title>Re: sharikrishna26.medium.com</title>
      <link>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14077#M8629</link>
      <description>&lt;P&gt;one other difference between those 2 approaches is that In Schema DDL String approach we use STRING, INT etc.. But In Struct Type Object approach we can only use Spark datatypes such as StringType(), IntegerType(), etc..&lt;/P&gt;</description>
      <pubDate>Mon, 02 Jan 2023 03:05:25 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/sharikrishna26-medium-com/m-p/14077#M8629</guid>
      <dc:creator>Varshith</dc:creator>
      <dc:date>2023-01-02T03:05:25Z</dc:date>
    </item>
  </channel>
</rss>

