I am new to python,can you help me with the details of how QVD can be read into azure databricks dataframe using python.
I need the detail syntax (authentication with access key)of accessing the QVD from datalake and the read the same using qvd_reader
Related
I was working on connecting dedicated sql pool(formerly sql DWH) to synapse spark notebooks. I was using spark.read.synapsesql(). I'm able to write data as table but not able to read data from the table.
val df:DataFrame = spark.read.option(Constants.SERVER, "XXXXX.database.windows.net")
.option(Constants.USER, "XXXXX")
.option(Constants.PASSWORD, "XXXXX")
.option(Constants.TEMP_FOLDER,"abfss://xxxxx#xxxx.dfs.core.windows.net/Tempfolder/")
.synapsesql("dedicated-poc.dbo.customer"
com.microsoft.spark.sqlanalytics.SQLAnalyticsConnectorException: com.microsoft.sqlserver.jdbc.SQLServerException: External file access failed due to internal error: 'Error occurred while accessing HDFS: Java exception raised on call to HdfsBridge_Connect.
Java exception message: Configuration property XXXXXXXX.dfs.core.windows.net not found.' at com.microsoft.spark.sqlanalytics.ItemsScanBuilder$PlanInputPartitionsUtilities$.extractDataAndGetLocation(ItemsScanBuilder.scala:183)
Permission: we have owner, storage data blob contributor access for synapse and specific user
To resolve the above exception, please try the below:
Try updating the code by adding below:
spark._jsc.hadoopConfiguration().set("fs.azure.account.key.xxxxx.dfs.core.windows.net", "xxxx==")
To read data from table, try including date data type in SQL Pool and then read.
Note:
Synapse RBAC roles do not grant permissions to create or manage SQL pools, Apache Spark pools, and Integration runtimes in Azure Synapse workspaces. Azure Owner or Azure Contributor roles on the resource group are required for these actions.
Give Azure owner role to resource group instead of synapse and specific user.
Check if there is any firewall rule that is blocking the connectivity and disable it.
If still the issue persists, raise a Azure support request
For more in detail, please refer below links:
Azure Synapse RBAC roles - Azure Synapse Analytics | Microsoft Docs
azure databricks - File read from ADLS Gen2 Error - Configuration property xxx.dfs.core.windows.net not found - Stack Overflow
I am using Azure Databricks, which I have hooked up to a data lake and I want to get metadata such as modified date for the files in the lake. I am able to do this within Databricks itself using os.stat() as detailed in this answer, but I am developing locally using Databricks connect, and can't figure out how to test it locally given it only has context of my local file system.
I'm using Azure CosmosDB SQL API and I'm looking a way to send data from CosmosDB to Google Big query. I'm
planning to use Kafka or Azure ADF for the same. I'm not sure this is correct approach/tools.
Is there any best practice or tool or connecter which I can use to send data from CosmosDB to Google Bigquery.
Data Factory supports Azure Cosmos DB (SQL API) as source and sink, but doesn't support Google Bigquery as the sink.
It means that we can not copy the data from Cosmos DB(SQL API) to Google Bigquery.
I wanted to load the data from Azure Blob storage to Azure SQL Database using Databricks notebook . Could anyone help me in doing this
I'm new to this, so I cannot comment, but why use Databricks for this? It would be much easier and cheaper to use Azure Data Factory.
https://learn.microsoft.com/en-us/azure/data-factory/tutorial-copy-data-dot-net
If you really need to use Databricks, you would need to either mount your Blob Storage account, or access it directly from your Databricks notebook or JAR, as described in the documentation (https://docs.azuredatabricks.net/spark/latest/data-sources/azure/azure-storage.html).
You can then read the files into DataFrames for whatever format they are in, and use the SQL JDBC connector to create a connection for writing the data to SQL (https://docs.azuredatabricks.net/spark/latest/data-sources/sql-databases.html).
I am trying to export CSV from Google cloud SQL to bucket. I want help to understand any bulk export mechanism, currently looks per instance we can export one CSV at one time.