I know how to set Spark configuration in a regular Databricks compute cluster. But I didn't see any place to set it in Databricks SQL endpoint.
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I would like to read data in Databricks with Spark outside of Databricks. But looks like there is no spark connector for Databricks available. Snowflake Connector for Spark is an example, I am looking for something similar for Databricks.
May I know what you mean by connectors ?
Databricks by itself will have the spark clusters running in it.
You can attach notebooks or run a spark job on top of it.
https://docs.databricks.com/notebooks/index.html
If you want to connect your local machine to databricks cluster and do development - you can try below databricks connect.
https://docs.databricks.com/dev-tools/databricks-connect.html
I am trying to install the Apache Spark Connector for SQL Server and Azure SQL to use transactional data in big data analytics and persists results for ad-hoc queries or reporting. The connector allows you to use any SQL database, on-premises or in the cloud, as an input data source or output data sink for Spark jobs.
The spark sql connector is located here https://github.com/microsoft/sql-spark-connector
Can someone let me know how to import it in Azure Synapse Apache Spark?
As per the conversation with Synapse Product Group:
You don’t need to add the connector Apache Spark connector jar files or any package com.microsoft.sqlserver.jdbc.spark to your Synapse Spark pool. The connector is there out of the box for Spark 2.4 and for Spark 3.1 it will be in production most likely in upcoming weeks.
For more details, refer to the Microsoft Q&A thread which addressing similar issue.
I am using a Spark Databricks cluster and want to add a customized Spark configuration.
There is a Databricks documentation on this but I am not getting any clue how and what changes I should make. Can someone pls share the example to configure the Databricks cluster.
Is there any way to see the default configuration for Spark in the Databricks cluster.
You can set cluster config in the compute section in your Databricks workspace.
Go to compute (and select cluster) > configuration > advanced options:
Or, you can set configs via a notebook.
%python
spark.conf.set("spark.sql.name-of-property", value)
Has anyone tried using Azure data bricks as the spark cluster for CDAP job processing. CDAP documentation details how to add it to Azure HDInsight, but just wondering is there a way to configure CDAP to point to data bricks spark cluster, is it even possible? OR this kind of integration needs a specific data bricks client connector jar? If anyone has any insights that would be helpful.
There is no out of box support for Databricks spark on Azure. But, that said you can develop a new Cloud Runtime that is capable of submitting the jobs to Databricks spark cluster. Here is example of how to write a runtime extension for Cloud Dataproc and EMR.
The Docs says "Every Databricks deployment has a central Hive metastore..." besides an external metastore for existing Hive installations.
I have an Azure Databricks workspace with an underlying spark cluster, and a datafiles stored on DBFS and Blob Storage. Do I need HDInsight cluster with external metastore to be able to create and use Hive tables? Or can I use the above mentioned central metastore to create Hive tables on data stored on DBFS or Blob storage?
#Gadam nope you do not. Azure Databricks provisions its own Hive Metastore, but if you are already using one with HDInsight, Databricks can be configured to also use it (an external metastore).