Is there a simple way to find out all the tables referenced in a stored procedure in azure analytics data warehouse other than parsing the stored procedure code? I tried few commands like sp_tables, sp_depends but none seems to be working in azure data warehouse.
sys.sql_expression_dependencies is supported in Azure Synapse Analytics, dedicated SQL pools, but only supports tables, views and functions at this time. A simple example:
SELECT * FROM sys.sql_expression_dependencies;
So you are left either parsing sys.sql_modules. Something like this is imperfect (ie doesn't deal with schema name, square brackets, partial matches etc) but could server as a starting point:
SELECT
sm.[definition],
OBJECT_SCHEMA_NAME(t.object_id) schemaName,
OBJECT_NAME(t.object_id) tableName
FROM sys.sql_modules sm
CROSS JOIN sys.tables t
WHERE sm.object_id = OBJECT_ID('dbo.usp_test')
AND sm.[definition] Like '%' + t.name + '%';
I actually use SQL Server Data Tools (SSDT) with dedicated SQL pools so your dependencies can't get out of step and are trackable via the project.
Related
I have some containers in ADLS (gen2) and have multiple folders within that container. I would like to have a mechanism to scan those folders to infer their schema and detect partitions and update them in the data catalog. How do I achieve this functionality in Azure?
Sample:
- container1
---table1-folder
-----10-12-1970
-------files1.parquet
-------files2.parquet
-------files3.parquet
-----10-13-1970
-------files1.parquet
-------files2.parquet
-------files3.parquet
-----10-14-1970
-------files1.parquet
-------files2.parquet
----table2-folder
-----zipcode1
-------files1.parquet
-------files2.parquet
-------files3.parquet
-----zipcode2
-------files1.parquet
-------files2.parquet
...
So, what I expect is that in the catalog, it will create two tables (table1 & table2) where table1 will have date-based partitions (3 dates for this case) and have underline data within that table. Same for table2 which will have two partitions and their underline data.
In the AWS world, I can run a Glue crawler that can crawl these files, infers schemas and partitions, and populate Glue data catalogs, later I can query them through Athena. What's the Azure equivalent approach to achieve something similar?
I would recommend looking at Azure Synapse Analytics Serverless SQL. You can create a view which consumes the folders and does partition elimination if you follow this approach:
-- If you do not have a Master Key on your DW you will need to create one
CREATE MASTER KEY ENCRYPTION BY PASSWORD = '<password>' ;
GO
CREATE DATABASE SCOPED CREDENTIAL msi_cred
WITH IDENTITY = 'Managed Service Identity' ;
GO
CREATE EXTERNAL DATA SOURCE ds_container1
WITH
( TYPE = HADOOP ,
LOCATION = 'abfss://container1#mystorageaccount.dfs.core.windows.net' ,
CREDENTIAL = msi_cred
) ;
GO
CREATE VIEW Table2
AS SELECT *, f.filepath(1) AS [zipcode]
FROM
OPENROWSET(
BULK 'table2-folder/*/*.parquet',
DATA_SOURCE = 'ds_container1',
FORMAT='PARQUET'
) AS f
Then setup Azure Purview as your data catalog and have it index your Synapse Serverless SQL pool.
I am using Azure Synapse to query a large number of CSV files with the OPENROWSET command see here. The files are located on a Data Lake gen 2 connected to the Azure Synapse via a managed identity.
This is working fine when I am only querying a few files at a time, however when I increase the number of files which I am trying to query simultaneousally I am getting the following error:
Azure Synapse: Cannot bulk load because the file <file> could not be opened. Operating system error code 12(The access code is invalid.)
Here <file> is a different file each time I run the query. If I navigate to the file in the linked data view I can download and view the file. Also if I specify to run the query on the file mentioned previousally in an error it will work fine.
The code I am using to query the data lake is below:
SELECT
Parsed.*
FROM OPENROWSET
(
bulk '2021/*/**.log',
maxerrors = 2147483647,
data_source = 'analytics',
format = 'csv',
fieldterminator ='0x0b',
fieldquote = '0x0b'
) WITH (doc nvarchar(max)) AS Rows
CROSS APPLY OPENJSON(Rows.doc)
WITH
(
col1 NVARCHAR(100),
col2 NVARCHAR(100),
...,
coln NVARCHAR(MAX)
) AS Parsed
Here the data source, analytics is a data source specified as follows:
CREATE EXTERNAL DATA SOURCE analytics
WITH
(
location = 'https://<url>.dfs.core.windows.net/analytics'
)
I have tried specifying a large number for the MAXERRORS parameter for BULK in OPENROWSET as I don't mind if only a few files are missed in executing this query, however this only seems to work at the row level for errors and these errors are at the file level.
The query is running here on the built-in serverless pool.
Any ideas on how to get around this issue would be appreciated.
Your code is doing pass through authentication to storage for whatever AAD user is connected to Synapse serverless (which will fail if you are using a SQL login). To use the MSI to connect to storage you will need a database scoped credential and will need to reference it in the external data source as in this example.
-- Optional: Create MASTER KEY if not exists in database:
-- CREATE MASTER KEY ENCRYPTION BY PASSWORD = '<Very Strong Password>
CREATE DATABASE SCOPED CREDENTIAL SynapseIdentity
WITH IDENTITY = 'Managed Identity';
GO
CREATE EXTERNAL DATA SOURCE mysample
WITH ( LOCATION = 'https://<storage_account>.dfs.core.windows.net/<container>/<path>',
CREDENTIAL = SynapseIdentity
)
Also see the sections in that article about the firewall on your storage account if you have that locked down.
Just adding a quick answer to this. After making the changes which Greg suggested, I was able to query a little more data - but still getting hit with the error code 12.
I spoke with Azure support and they advised me that the error message was actually 412 (but it was not visable to me); so this implied file in use/being modified. Adding the following allowed Azure Synapse to ignore this and query the file regardless:
ROWSET_OPTIONS = '{"READ_OPTIONS":["ALLOW_INCONSISTENT_READS"]}'
or for external tables:
TABLE_OPTIONS = N'{"READ_OPTIONS":["ALLOW_INCONSISTENT_READS"]}'
This made my final query:
SELECT
Parsed.*
FROM OPENROWSET
(
bulk '2021/*/**.log',
maxerrors = 2147483647,
data_source = 'analytics_master_key',
format = 'csv',
fieldterminator ='0x0b',
fieldquote = '0x0b',
ROWSET_OPTIONS = '{"READ_OPTIONS":["ALLOW_INCONSISTENT_READS"]}'
) WITH (doc nvarchar(max)) AS Rows
CROSS APPLY OPENJSON(Rows.doc)
WITH
(
col1 NVARCHAR(100),
col2 NVARCHAR(100),
...,
coln NVARCHAR(MAX)
) AS Parsed
I'm trying to do a simple incremental update from an on-prem database as source to Azure SQL database based on a varchar column called "RP" in On-Prem database that contains "date+staticdescription" for example: "20210314MetroFactory"
1- I've created a Lookup activity called Lookup1 using a table created in Azure SQL Database and uses this Query
"Select RP from SubsetwatermarkTable"
2- I've created a Copy data activity where the source settings have this Query
"Select * from SourceDevSubsetTable WHERE RP NOT IN '#{activity('Lookup1').output.value}'"
When debugging -- I'm getting the error:
Failure type: User configuration issue
Details: Failure happened on 'Source' side.
'Type=System.Data.SqlClient.SqlException,Message=Incorrect syntax near
'[{"RP":"20210307_1Plant
1KAO"},{"RP":"20210314MetroFactory"},{"RP":"20210312MetroFactory"},{"RP":"20210312MetroFactory"},{"RP":"2'.,Source=.Net
SqlClient Data
Provider,SqlErrorNumber=102,Class=15,ErrorCode=-2146232060,State=1,Errors=[{Class=15,Number=102,State=1,Message=Incorrect
syntax near
'[{"RP":"20210311MetroFactory"},{"RP":"20210311MetroFactory"},{"RP":"202103140MetroFactory"},{"RP":"20210308MetroFactory"},{"RP":"2'.,},],'
Can anyone tell me what I am doing wrong and how to fix it even if it requires creating more activities.
Note: There is no LastModifiedDate column in the table. Also I haven't yet created the StoredProcedure that will update the Lookup table when it is done with the incremental copy.
Steve is right as to why it is failling and the query you need in the Copy Data.
As he says, you want a comma-separated list of quoted values to use in your IN clause.
You can get this more easily though - from your Lookup directly using this query:-
select stuff(
(
select ','''+rp+''''
from subsetwatermarktable
for xml path('')
)
, 1, 1, ''
) as in_clause
The sub-query gets the comma separated list with quotes around each rp-value, but has a spurious comma at the start - the outer query with stuff removes this.
Now tick the First Row Only box on the Lookup and change your Copy Data source query to:
select *
from SourceDevSubsetTable
where rp not in (#{activity('lookup').output.firstRow.in_clause})
The result of #activity('Lookup1').output.value is an array like your error shows
[{"RP":"20210307_1Plant
1KAO"},{"RP":"20210314MetroFactory"},{"RP":"20210312MetroFactory"},{"RP":"20210312MetroFactory"},{"RP":"2'.,Source=.Net
SqlClient Data
Provider,SqlErrorNumber=102,Class=15,ErrorCode=-2146232060,State=1,Errors=[{Class=15,Number=102,State=1,Message=Incorrect
syntax near
'[{"RP":"20210311MetroFactory"},{"RP":"20210311MetroFactory"},{"RP":"202103140MetroFactory"},{"RP":"20210308MetroFactory"},{"RP":"2'.,},]
However, your SQL should be like this:Select * from SourceDevSubsetTable WHERE RP NOT IN ('20210307_1Plant 1KAO','20210314MetroFactory',...).
To achieve this in ADF, you need to do something like this:
create three variables like the following screenshot:
loop your result of #activity('Lookup1').output.value and append 'item().RP' to arrayvalues:
expression:#activity('Lookup1').output.value
expression:#concat(variables('apostrophe'),item().RP,variables('apostrophe'))
3.cast arrayvalues to string and add parentheses by Set variable activity
expression:#concat('(',join(variables('arrayvalues'),','),')')
4.copy to your Azure SQL database
expression:Select * from SourceDevSubsetTable WHERE RP NOT IN #{variables('stringvalues')}
I am trying to get the count of all records present in cosmos db in a lookup activity of azure data factory. I need this value to do a comparison with other value activity outputs.
The query I used is SELECT VALUE count(1) from c
When I try to preview the data after inserting this query I get an error saying
One or more errors occurred. Unable to cast object of type
'Newtonsoft.Json.Linq.JValue' to type 'Newtonsoft.Json.Linq.JObject'
as shown in the below image:
snapshot of my azure lookup activity settings
Could someone help me in resolving this error and if this is the limitation of azure data factory how can I get the count of all the rows of the cosmos db document using some other ways inside azure data factory?
I reproduce your issue on my side exactly.
I think the count result can't be mapped as normal JsonObject. As workaround,i think you could just use Azure Function Activity(Inside Azure Function method ,you could use SDK to execute any sql as you want) to output your desired result: {"number":10}.Then bind the Azure Function Activity with other activities in ADF.
Here is contradiction right now:
The query sql outputs a scalar array,not other things like jsonObject,or even jsonstring.
However, ADF Look Up Activity only accepts JObject,not JValue. I can't use any convert built-in function here because the query sql need to be produced with correct syntax anyway. I already submitted a ticket to MS support team,but get no luck with this limitation.
I also tried select count(1) as num from c which works in the cosmos db portal. But it still has limitation because the sql crosses partitions.
So,all i can do here is trying to explain the root cause of issue,but can't change the product behaviours.
2 rough ideas:
1.Try no-partitioned collection to execute above sql to produce json output.
2.If the count is not large,try to query columns from db and loop the result with ForEach Activity.
You can use:
select top 1 column from c order by column desc
I have a very simple ADF pipeline to copy data from local mongoDB (self-hosted integration environment) to Azure SQL database.
My pipleline is able to copy the data from mongoDB and insert into SQL db.
Currently if I run the pipeline it inserts duplicate data if run multiple times.
I have made _id column as unique in SQL database and now running pipeline throws and error because of SQL constraint wont letting it insert the record.
How do I check for duplicate _id before inserting into SQL db?
should I use Pre-copy script / stored procedure?
Some guidance / directions would be helpful on where to add extra steps. Thanks
Azure Data Factory Data Flow can help you achieve that:
You can follow these steps:
Add two sources: Cosmos db table(source1) and SQL database table(source2).
Using Join active to get all the data from two tables(left join/full join/right join) on Cosmos table.id= SQL table.id.
AlterRow expression to filter the duplicate _id, it not duplicate then insert it.
Then mapping the no-duplicate column to the Sink SQL database table.
Hope this helps.
You Should implement your SQL Logic to eliminate duplicate at the Pre-Copy Script
Currently I got the solution using a Stored Procedure which look like a lot less work as far this requirement is concerned.
I have followed this article:
https://www.cathrinewilhelmsen.net/2019/12/16/copy-sql-server-data-azure-data-factory/
I created table type and used in stored procedure to check for duplicate.
my sproc is very simple as shown below:
SET QUOTED_IDENTIFIER ON
GO
ALTER PROCEDURE [dbo].[spInsertIntoDb]
(#sresults dbo.targetSensingResults READONLY)
AS
BEGIN
MERGE dbo.sensingresults AS target
USING #sresults AS source
ON (target._id = source._id)
WHEN NOT MATCHED THEN
INSERT (_id, sensorNumber, applicationType, place, spaceType, floorCode, zoneCountNumber, presenceStatus, sensingTime, createdAt, updatedAt, _v)
VALUES (source._id, source.sensorNumber, source.applicationType, source.place, source.spaceType, source.floorCode,
source.zoneCountNumber, source.presenceStatus, source.sensingTime, source.createdAt, source.updatedAt, source.updatedAt);
END
I think using stored proc should do for and also will help in future if I need to do more transformation.
Please let me know if using sproc in this case has potential risk in future ?
To remove the duplicates you can use the pre-copy script. OR what you can do is you can store the incremental or new data into a temp table using copy activity and use a store procedure to delete only those Ids from the main table which are in temp table after deletion insert the temp table data into the main table. and then drop the temp table.