I have a json file stored in Azure Blob Storage and I have loaded it into Azure SQL DB using Data Factory.
Now I would like to find a way in order to load only new records from the file to my database (as the file is being updated every week or so). Is there a way to do it?
Thanks!
You can use the upsert ( slowly changing dimension type 1 ) that is already implemented in Azure Data Factory.
It will add new record and update old record that changed.
Here a quick tutorial :
https://www.youtube.com/watch?v=MzHWZ5_KMYo
I would suggest you to use Dataflow activity.
In Dataflow Activity, you have the option of alter row as shown in below image.
In Alter row you can use Upsert if condition.
Here mention condition as 1 == 1
Related
I'm developing a pipeline that be able to insert data from a .txt file located in the Blob Storage into a table in a SQL Data Base.
Problem: Somehow the activity configuration is not working properly cause' is not reading all the records in the file and in consequence is not loading all the data into the Data Base (I realized this issue when I opened the file and compared the number of records from .text file against SQL table. Also, when I searched records from the last month in the table on SQL I didn't find them)
Note: I checked out the size limit of characters in the table from SQL and that isn't the problem.
I'd like to share with you the Data Copy activity and Source Data Set configuration as well:
Sink Dataset:
Do you know, guys what I'm doing wrong here? Hope you can help me, best regards.
P.S. Here's the Source Dataset
As discussed in comments, while using copy activity you would have to make sure to set the schema before running the activity. By design the schema mapping is left empty and has to be configured by the user either manually or asking adf to import the schema from the dataset.
Note: While using Auto create table option in sink, it automatically creates sink table (if nonexistent) in source schema,
but won't be supported when a stored procedure is specified (on the
sink side) or when staging is enabled.
Using COPY statement to load data into Azure Synapse Analytics as sink, the connector supports automatically creating destination table with DISTRIBUTION = ROUND_ROBIN if not exists based on the source schema.
Refer official doc: Copy and transform data in Azure Synapse Analytics by using Azure Data Factory or Synapse pipelines
Source...
Sink...
So Azure Synapse will be used as the sink. Additionally, an Azure Synapse table has to be created which matches the column names, column order, and column data types of source.
For dynamic mapping
If you view the pipeline code, you can see in the Translator section the JSON equivalent of the mapping section from UI.
You can reuse this as a base in Dynamic mapping to enable further copying similar files without having to manually configure schema.
Copy the JSON under mappings in translator
I am building Azure IoT solution for my BI project. For now I have an application that once per set time window sends a .csv blob to Azure Blob Storage with incremental number in name. So after some time I will have in my storage files such as 'data1.csv', 'data2.csv', 'data3.csv', etc.
Now I will need to load these data into a database which will be my warehouse with the use of Azure Stream Analytics job. The issue might be that .CSV files will have overlapping data. They will be send every 4h and contain data for past 24h. I need to always read only last file (with highest number) and prepare lookup so it properly updates data in the warehouse. What will be the best approach to make Stream Analytics read only latest file and for updating records in DB?
EDIT:
TO clarify - I am fully aware that ASA is not capable of being an ETL job. My question is what would be best approach for my case with using IoT tools
I would suggest one of these 2 ways:
use ASA to write in a temporary SQL table, and the use a SQL trigger
to update the main table of the DW with the diff.
Or remove duplicates by adding a unique constraint as described here:
https://blogs.msdn.microsoft.com/streamanalytics/2017/01/13/how-to-achieve-exactly-once-delivery-for-sql-output/
Thanks,
JS - Azure Stream Analytics
I am currently working on azure data lake with snappy-data integration,I have a query on snappy-data are we able to update the data in the snappy-data to azure data lake storage, or we can append only on the azure data lake storage i searched in forum but i can't reach for that proper solution on it,if any one know about that query on it please share it,thank you.
Azure Data Lake Store, much like HDFS, is an append only store. You can append to a file or replace it altogether. There is no way to update an existing file.
I've achieved MERGE style behaviour in USQL by using a Azure Data Lake table as the middle ground between input and output. Check out my blog post with the code showing how I did it with a series of joins.
https://www.purplefrogsystems.com/paul/2016/12/writing-a-u-sql-merge-statement/
This will give you append behaviour in your output.
I'm trying to understand the best way to migrate a large set of data - ~ 6M text rows from (an Azure Hosted) SQL Server to Blob storage.
For the most part, these records are archived records, and are rarely accessed - blob storage made sense as a place to hold these.
I have had a look at Azure Data Factory and it seems to be the right option, but I am unsure of it fulfilling requirements.
Simply the scenario is, for each row in the table, I want to create a blob, with the contents of 1 column from this row.
I see the tutorial (i.e. https://learn.microsoft.com/en-us/azure/data-factory/data-factory-copy-activity-tutorial-using-azure-portal) is good at explaining migration of bulk-to-bulk data pipeline, but I would like to migrate from a bulk-to-many dataset.
Hope that makes sense and someone can help?
As of now, Azure Data Factory does not have anything built in like a For Each loop in SSIS. You could use a custom .net activity to do this but it would require a lot of custom code.
I would ask, if you were transferring this to another database, would you create 6 million tables all with the same structure? What is to be gained by having the separate items?
Another alternative might be converting it to JSON which would be easy using Data Factory. Here is an example I did recently moving data into DocumentDB.
Copy From OnPrem SQL server to DocumentDB using custom activity in ADF Pipeline
SSIS 2016 with the Azure Feature Pack, giving Azure Tasks such as Azure Blob Upload Task and Azure Blob Destination. You might be better off using this, maybe an OLEDB command or the For Each loop with an Azure Blob destination could be another option.
Good luck!
Azure has a ForEach activity which can be place after LookUp or Metadata to get the each row from SQL to blob
ForEach
While moving data from Table Storage to SQL Azure, is it possible to obtain only the Delta (The data that hasn't been already moved) using Azure Data Factory?
A more detailed explanation:
There is an Azure Storage Table, which contains some data, which will be updated periodically. And I want to create a Data Factory pipeline which moves this data to an SQL Azure Database. But during each move I only want the newly added data to be written to SQL DB. Is it possible with Azure Data Factory?
See more information on azureTableSourceQuery and copy activity at this link : https://azure.microsoft.com/en-us/documentation/articles/data-factory-azure-table-connector/#azure-table-copy-activity-type-properties.
Also see this link for invoking stored procedure for sql: https://azure.microsoft.com/en-us/documentation/articles/data-factory-azure-sql-connector/#invoking-stored-procedure-for-sql-sink
You can query each time on timestamp to achieve something similar to delta copy, but this is not true delta copy.