I want to download all SQL scripts on Databricks SQL so that I can put them in a Git repository. Is there a way to download all of them programmatically? Alternatively, can someone guide me to their location on DBFS?
Thanks.
There is a REST API for Databricks SQL queries that you can use to export queries.
P.S. SQL queries aren't stored on DBFS
Related
I am thinking about using Snowflake as data warehouse. My databases are in Azure SQl Database and I would like to know what tools I need for etl my data from Azure SQL Database to Snowflake.
I think Snowpark could work for data transformations, but I wonder what other code tool could I use.
Also, I wonder if I use azure blob storage as staging area or snowflake has its own.
Thanks
You can use HEVO data a third-party tool where you can directly migrate data from Microsoft SQL Server to Snowflake.
STEPS TO BE FOLLOWED
Make a connection to your Microsoft SQL Server database.
Choose a replication mode.
Create a Snowflake Data Warehouse configuration.
Alternatively, You can use SnowSQL to Connect Microsoft SQL Server to Snowflake where you export data from SQL Server to SSMS, upload the same to either Azure storage or S3, and move the data from Storage to Snowflake.
REFERENCES:
Microsoft SQL Server to Snowflake
How to move the data from Azure Blob Storage to Snowflake
I am trying to migrate my on premise SQL Server views which has fewer joins to extract the output. I have extracted the views ddl through generate script but when ran it on Azure Synapse it's not working please help
I want to copy the Data from the AzureCosmosDb Database\Container to the Local.
I am trying with the Azcopy tool. I have tried the query as per this URL. But its not working.
The query which I have tried is as below :
Azcopy /Source:<Endpoint\Database\Container> /SourceKey:key /"<PrimaryKey>" /Dest:<Local Location> /EntityOperation:InsertOrReplace
What should I have to modify in this query to get the Data from Cosmos Db to my Local folder ?
The above method is recommended for Table API as mentioned in the doc, if you want to migrate data of SQL API use the Data Migration Tool.
I creating Data Factory Pipeline to Load Initial and Incremental into Data Lake from Az MySql database to an Az SQL Server database.
Initial Pipeline to load data from MySql to Data Lake is all good. Is being persisted as .parquet files.
Now I need to load these into a SQL Server table with some basic type conversions. What is the best way?
Databricks => mount these .parquet files, standardised and load into SQL Server tables?
Or can I create an external source to these files in SQL Server on Azure and do standardisation. We are not on Synapse (dwh) yet.
Or is there better way?
Since you are already using ADF , you can explore Mapping data flow .
https://learn.microsoft.com/en-us/azure/data-factory/concepts-data-flow-overview
I am trying to read data from databricks delta lake via. apache superset. I can connect to delta lake with a JDBC connection string supplied by the cluster but superset seems to require a sql alchemy string so I'm not sure what I need to do to get this working. Thank you, anything helps
superset database setup
Have you tried this?
https://flynn.gg/blog/databricks-sqlalchemy-dialect/
Thanks to contributions by Evan Thomas, the Python databricks-dbapi
package now supports using Databricks as a SQL dialect within
SQLAlchemy. This is particularly useful for hooking up Databricks to a
dashboard frontend application like Apache Superset. It provides
compatibility with both standard Databricks and Azure Databricks.
Just use pyhive and you should be ready to connect to databricks thrift JDBC server.