I have a linked service that connects to an on-prem Oracle database through a self hosted integration runtime.
I am able to access this from a data factory pipeline - the dataset that uses the linked service is called pc_payinitil.
However, the pc_payinitial dataset is not available to select from the sink tab of a sink shape of a data flow:
Am I trying to do something that's not possible - or did I just go wrong somewhere?
Currently, the Oracle dataset is not supported in mapping data flow in the Azure data factory. It is only supported in copy activity source/sink and lookup activity.
There are only limited datasets that are supported in mapping data flow as of now. You can go through this MS document for more information on supported data stores in the Azure data factory.
Related
Please help me with copying data from Google BigQuery to Azure Data Lake Storage Gen2 with Serverless SQL Pool.
I am using Azure Synapse's Copy data pipeline. The issue is I cannot figure out how to handle source table from the BigQuery with hierarchical schema. This result in missing columns and inaccurate datetime value at the sink.
The source is a Google BigQuery table, it is made of Google Cloud Billing export of a project's standard usage cost. The source table's schema is hierarchical with nested columns, such as service.id; service.description; sku.id; sku.description; Project.labels.key; Project.labels.value, etc.
When I click on Preview data from the Source tab of the Copy data pipeline, it only gives me the top of the column hierarchy, for example: It would only show the column name of [service] and with value of {\v":{"f":[{"v":"[service.id]"},{"v":"[service.descrpition]"}]}}
image description: Source with nested columns result in issues with Synapse Copy Data Pipline
I have tried to configure the Copy Pipline with the following:
Source Tab:
Use query - I think the solution lays in here, but I cannot figure out the syntax of selecting the proper columns. I watched a Youtube video from TechBrothersIT How to Pass Parameters to SQL query in Azure Data Factory - ADF Tutorial 2021, but still unable to do it.
Sink Tab:
1.Sink dataset in various format of csv, json and parquet - with csv and parquet getting similar result, and json format failed
2.Sink dataset to Azure SQL Database - failed because it is not supported with Serverless SQL Pool
3.Mapping Tab: note: edited on Jan22 with screenshot to show issue.
Tried with Import schemas, with Sink Tab copy behavior of None, Flatten Hierarchy and Preserve Hierarchy, but still unable to get source column to be recognized as Hierarchical. Unable to get the Collection reference nor the Advanced Editor configurations to show up. Ref: Screenshot of Source columns not detected as Hierarchical MS Doc on Schema and data type mapping in copy activity
I have also tried with the Data flow pipeline, but it does not support Google BigQueryData Flow Pipe Source do not support BigQuery yet
Here are the steps to reproduce / get to my situation:
Register Google cloud, setup billing export (of standard usage cost) to BigQuery.
At Azure Synapse Analytics, create a Linked service with user authentication. Please follow Data Tech's Youtube video
"Google BigQuery connection (or linked service) in Azure Synapse analytics"
At Azure Synapse Analytics, Integrate, click on the "+" sign -> Copy Data Tool
I believe the answer is at the Source tab with Query and Functions, please help me figure this out, or point me to the right direction.
Looking forward to your input. Thanks in advance!
ADF allows you to write the query in google bigquery source dataset. Therefore write the query to unnest the nested columns using unnest operator and then map it to the sink.
I tried to repro this with sample nested table.
img:1 nested table
img:2 sample data of nested table
Script to flatten the nested table:
select
user_id,
a.post_id,
a.creation_date
from `ds1.stackoverflow_nested`
cross join unnest(comments) a
img:3 flattened table.
Use this query in copy activity source dataset.
img:4 Source settings of copy activity.
Then take the sink dataset, do the mapping and execute the ADF pipeline.
Reference:
MS document on google bigquery as a source - ADF
GC document on unnest operator
I want to implement the scd2 in the snowflake tables. My source and target tables are present in snowflake only. The entire process has to be done using Azure Data Factory.
I went through the documentation given by azure for implementing the scd2 using data flows but when I tried to create a dataset for snowflake connection its showing as disabled.
Is there any way or any documentation where I can see the steps to create SCD2 in adf with snowflake tables.
Thanks
vipendra
SCD2 in ADF can be built and managed graphically via data flows. The Snowflake connector for ADF today does not work directly with data flows, yet. So for now, you will need to use the Copy Activity in an ADF pipeline and stage the dimension data in Blob or ADLS, then build your SCD2 logic in data flows using the staged data.
Your pipeline will look something like this:
[Copy Activity Snowflake-to-Blob] -> [Data Flow SCD2 logic Blob-to-Blob] -> [Copy Activity Blob-to-Snowkflake]
We are working on direct connectivity to Snowflake from data flows and hope to land that soon.
If your source and target tables are both in Snowflake, you could use Snowflake Streams to do this. There's a blog post covering this in more detail at https://community.snowflake.com/s/article/Building-a-Type-2-Slowly-Changing-Dimension-in-Snowflake-Using-Streams-and-Tasks-Part-1
However, in short, if you have a source table source, you can put a stream on it like so:
create or replace stream source_changes on table source;
This will capture all the changes that are made to the source table. You can then build a view on that stream that establishes how you want to feed those changes into the SCD table. (The blog post uses case statements to put start and end dates in on each row in the view).
From there, you can use a Snowflake Task to automate the process of loading from the stream into the SCD only when the Stream actually has changes.
I have a copy data activity for on-premise SQL Server as source and ADLS Gen2 as sink. There is a control table to pickup tableName, watermarkDateColumn and the watermarkDatetime to pull incremental data from the source database.
After data is pulled/loaded in sink, I want to get the max of the watermarkDateColumn in my dataset. Can it be obtained from #activity('copyActivity1').output?
I'm not allowed to use one extra lookup activity to query the source table for getting the max(watermarkDateColumn) in pipeline.
Copy activity only could be used for data transmission,not for any other aggregation feature. So #activity('copyActivity1').output won't help. Since you said you can't use lookup activity, i'm afraid your requirement is not available so far.
If you prefer not using additional activities, I suggest you using Data Flow Activity instead which is more flexible.There is built-in aggregation feature in the Data Flow Activity.
I am accessing Databricks Delta tables from Azure Data Factory, which does not have a native connector to Databricks tables. So, as a workaround, I create the tables with the LOCATION keyword to store them in Azure Data Lake. Then, since I know the table file location, I just read the underlying Parquet files from Data Factory. This works fine.
But... what if there is cached information in the Delta transaction log that has not yet been written to disk? Say, an application updated a row in the table, and the disk does not yet reflect this fact. Then my read from Data Factory will be wrong.
So, two questions...
Could this happen? Are changes held in the log for a while before being written out?
Can I force a transaction log flush, so I know the disk copy is updated?
Azure Data Factory has built in delta lake support (this was not the case at the time the question was raised).
Delta is available as an inline dataset in a Azure Data Factory data flow activity. To get column metadata, click the Import schema button in the Projection tab. This will allow you to reference the column names and data types specified by the corpus (see also the docs here).
ADF supports Delta Lake format as of July 2020:
https://techcommunity.microsoft.com/t5/azure-data-factory/adf-adds-connectors-for-delta-lake-and-excel/ba-p/1515793
The Microsoft Azure Data Factory team is enabling .. and a data flow connector for data transformation using Delta Lake
Delta is currently available in ADF as a public preview in data flows as an inline dataset.
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Hi Stack team,
actually i plan to migrate my SQL server2012 databases to Azure data warehouse with Azure data factory approach...
But problems are,
1) my database size is 4.5 TB
2)in this approach there are 3 methods. those method details i mentioned in the attached image.. my problem is i planed to 3rd method for migrate(3.Using Azure Data Factory and PowerShell (entire database - ADF))
so please tell me links related above method and its possible for migration or not. if its possiable send me how to do...
Please refers to the link below, there's an UX solution in Azure Data Factory which are just target for migration from SQL Server to Azure SQL Datawarehouse. It's a wizard based UX which are very easy to follow. It will automatically create tables in Azure SQL Datawarehouse and migrate the data using polybase, which is the most efficient way to load data into SQLDW.
https://learn.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-with-data-factory