<?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: Fastest Azure VM for Databricks Big Data workload in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/fastest-azure-vm-for-databricks-big-data-workload/m-p/8105#M3823</link>
    <description>&lt;P&gt;@Alvaro Moure​&amp;nbsp;:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The performance of a Databricks cluster for big data operations depends on many factors, such as the amount and structure of the data, the nature of the operations being performed, the configuration of the cluster, and the specific resources available in each VM family.&lt;/P&gt;&lt;P&gt;That being said, the LasV3 family of VMs in Azure Databricks does offer some of the highest performing options for big data operations due to their large memory and high CPU power. However, this also makes them more expensive than other options. It's also worth noting that different use cases may have different requirements, and a smaller or less powerful cluster may be sufficient for certain tasks.&lt;/P&gt;&lt;P&gt;Ultimately, the best way to determine the fastest cluster for your specific use case is to benchmark and compare performance across different VM families and configurations. &lt;/P&gt;</description>
    <pubDate>Thu, 16 Mar 2023 07:56:30 GMT</pubDate>
    <dc:creator>Anonymous</dc:creator>
    <dc:date>2023-03-16T07:56:30Z</dc:date>
    <item>
      <title>Fastest Azure VM for Databricks Big Data workload</title>
      <link>https://community.databricks.com/t5/data-engineering/fastest-azure-vm-for-databricks-big-data-workload/m-p/8104#M3822</link>
      <description>&lt;P&gt;Hi All,&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;It is well known that Azure provides a wide variety of VM for Databricks, some of which provide powerful features such as Photon and Delta Caching. I would like to ask the community which do you think is the fastests cluster for performing Big Data operations (in the order of TB) among all the available options. In my opinion LasV3 family seems to be the best but I would like additional opinions.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;Thanks in advance.&lt;/P&gt;</description>
      <pubDate>Wed, 08 Mar 2023 08:13:40 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/fastest-azure-vm-for-databricks-big-data-workload/m-p/8104#M3822</guid>
      <dc:creator>alvaro_databric</dc:creator>
      <dc:date>2023-03-08T08:13:40Z</dc:date>
    </item>
    <item>
      <title>Re: Fastest Azure VM for Databricks Big Data workload</title>
      <link>https://community.databricks.com/t5/data-engineering/fastest-azure-vm-for-databricks-big-data-workload/m-p/8105#M3823</link>
      <description>&lt;P&gt;@Alvaro Moure​&amp;nbsp;:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;The performance of a Databricks cluster for big data operations depends on many factors, such as the amount and structure of the data, the nature of the operations being performed, the configuration of the cluster, and the specific resources available in each VM family.&lt;/P&gt;&lt;P&gt;That being said, the LasV3 family of VMs in Azure Databricks does offer some of the highest performing options for big data operations due to their large memory and high CPU power. However, this also makes them more expensive than other options. It's also worth noting that different use cases may have different requirements, and a smaller or less powerful cluster may be sufficient for certain tasks.&lt;/P&gt;&lt;P&gt;Ultimately, the best way to determine the fastest cluster for your specific use case is to benchmark and compare performance across different VM families and configurations. &lt;/P&gt;</description>
      <pubDate>Thu, 16 Mar 2023 07:56:30 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/fastest-azure-vm-for-databricks-big-data-workload/m-p/8105#M3823</guid>
      <dc:creator>Anonymous</dc:creator>
      <dc:date>2023-03-16T07:56:30Z</dc:date>
    </item>
  </channel>
</rss>

