Is there a recommended solution for storing metadata of table/file schemas while using Azure Synapse Analytics Spark Pools. data will be written in either parquet/delta table format.
Thank you
Please Follow below reference it has a detailed explanation about storing metadata of table using Azure Synapse Spark Pool and configure Spark to use the external Hive Metastore.
Reference:
External Hive Metastore for Synapse Spark Pool by Microsoft
Related
We are currently extracting multiple tables from Azure SQL Servereless pool in Synapse. Unlike a regular Azure SQL Database it is very easy to increase the performance from Basic all the way through to Premium or Business continuity.
Can someone let me know how to go about increasing the performance of Azure SQL Serverles Pool in synapse?
Serverless SQL pool is a distributed data processing system and it doesn't have any inbuilt storage to store data. It uses external table to query the data from Azure data lake storage. Therefore, data cannot be copied to the serverless SQL pool. If data needs to be extracted from serverless SQL pool, you can extract data directly from the underlying external storage. If the target datastore supports polybase data loading, use that to load to the target table from ADLS.
I try to use Serverless Sql Pool Integration dataset in Azure Analitycs DataFlow as a source but I can't. SQL Pool is unavailable as a Source in DataFlow, but I don't know why?
What is a problem? I use SQL Pool datasets in Azure Synapse Pipelines and it works. Is it problem with my licence, version or maybe I do something wrong?
Have you tried selecting Synapse Dataset instead of SQL
You will need a Synapse Linked Service as well
I am quite new to databricks and looking for a smart way to export a data table from databricks gold scheme to an azure sql database.
I am using databricks as a part of azure resource group, however I do not find data from databricks in any of the storage accounts that are within the same resource group. Does it mean that is is physically stored at en implicit databricks storage account/data lake?
Thanks in advance :-)
The tables you see in Databricks could be have the data stored within that Databricks Workspace file system (DBFS) or somewhere external (e.g. Data Lake, which could be in a different Azure Resource Group) - see here: Databricks databases and tables
For writing data from Databricks to Azure SQL, I would suggest the Apache Spark connector for SQL.
It is possible to read data from Azure blob storage in Azure SQL database via openrowset or bulkinsert.
But is it possible to upload a file in blob through any SQL commands in Azure SQL DB ?
Similar to CETAS in Azure Synapse.
Unfortunately, that seems to be current limitation for SQLDB. below link has the details PolyBase features and limitations
On HDFS Hive ORC ACID for Hive MERGE no issue.
On S3 not possible.
For Azure HD Insight I am not clear from docs if such a table on Azure Blob Storage is posible? Seeking confirmation or otherwise.
I am pretty sure no go. See the update I gave on the answer, however.
According to Azure HDInsight offical documents Azure HDInsight 4.0 overview as the figure below,
As I known, Hive MERGE requires MapReduce, but HDInsight does not support it for Hive, so it's also not possible.
UPDATE by question poster
HDInsight 4.0 doesn't support MapReduce for Apache Hive. Use Apache Tez instead. So, with Tez it will still work and from https://learn.microsoft.com/en-us/azure/hdinsight/hdinsight-version-release Spark with Hive 3 and Warehouse Connector are also options.