In Storage Table I have dynamicaly generated PartitionKey in YYYY-MM-DD-HH format. And I need querying this in Data Factory Pipeline
I need something like this:
PartitionKey eq DateTime.Now.ToString("yyyyMMddHH")
It is possible? Thanks ...
You could use formatDateTime dynamic date functions in ADF.
TEST:
configuration:
output:
UPDATE:
Sorry for my uncompletely answer.I figured it out by using below expression:
#concat('PartitionKey eq ''', variables('dateValue'),'''')
Screenshot:
Entire structure:
I got some clues from this link,also provide for you:Azure Data Factory Expression Query for Copy activity.
Related
I have an Azure Stream Analytics job that uses an EventHub and a Reference data in Blob storage as 2 inputs. The reference data is CSV that looks something like this:
REGEX_PATTERN,FRIENDLY_NAME
115[1-2]{1}9,Name 1
115[3-9]{1}9,Name 2
I then need to lookup an attribute in the incoming event in EventHub against this CSV to get the
FRIENDLY_NAME.
Typical way of of using reference data is using JOIN clause. But in this case I cannot use it because such regex matching is not supported with LIKE operator.
UDF is another option, but I cannot seem to find a way of using reference data as a CSV inside the function.
Is there any other way of doing this in an Azure Stream Analytics job?
As I know, the JOIN is not supported in your scenario. The join key should be specific, can't be a regex value.
Thus, reference data is not suitable here because it should be used in the ASA sql like below:
SELECT I1.EntryTime, I1.LicensePlate, I1.TollId, R.RegistrationId
FROM Input1 I1 TIMESTAMP BY EntryTime
JOIN Registration R
ON I1.LicensePlate = R.LicensePlate
WHERE R.Expired = '1'
The join key is needed. What I mean is that the reference data input is not needed even here.
Your idea is using UDF script and load the data in the UDF to compare with the hardcode regex data. This idea is not easy to maintain. Maybe you could consider my workaround:
1.You said you have different reference data,please group them and store as json array. Assign one group id to every group. For example:
Group Id 1:
[
{
"REGEX":"115[1-2]{1}9",
"FRIENDLY_NAME":"Name 1"
},
{
"REGEX":"115[3-9]{1}9",
"FRIENDLY_NAME":"Name 2"
}
]
....
2.Add one column to referring group id and set Azure Function as Output of your ASA SQL. Inside Azure Function, please accept the group id column and load the corresponding group of json array. Then loop the rows to match the regex and save the data into destination residence.
I think Azure Function is more flexible then UDF in ASA sql job. Additional,this solution is maybe easier to maintain.
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.
I have a cosmos DB collection in the following format:
{
"deviceid": "xxx",
"partitionKey": "key1",
.....
"_ts": 1544583745
}
I'm using Azure Data Factory to copy data from Cosmos DB to ADLS Gen 2. If I copy using a copy activity, it is quite straightforward. However, my main concern is the output path in ADLS Gen 2. Our requirements state that we need to have the output path in a specific format. Here is a sample of the requirement:
outerfolder/version/code/deviceid/year/month/day
Now since deviceid, year, month, day are all in the payload itself I can't find a way to use them except create a lookup activity and use the output of the lookup activity in the copy activity.
And this is how I set the ouput folder using the dataset property:
I'm using SQL API on Cosmos DB to query the data.
Is there a better way I can achieve this?
I think that your way works, but its not the cleanest. What I'd do is create a different variable inside the pipeline for each one: version, code, deviceid, etc. Then, after the lookup you can assign the variables, and finally do the copy activity referencing the pipeline variables.
It may look kind of redundant, but think of someone (or you 2 years from now) having to modify the pipeline and if you are not around (or have forgotten), this way makes it clear how it works, and what you should modify.
Hope this helped!!
Cannot find an answer via google, msdn (and other microsoft) documentation, or SO.
In Azure Data Factory you can get data from a dataset by using copy activity in a pipeline. The pipeline definition includes a query. All the queries I have seen in documentation are simple, single table queries with no joins. In this case, a dataset is defined as a table in the database with "TableName"= "mytable". Additionally, one could retrieve data from a stored procedure, presumably allowing more complex sql.
Is there a way to define a more complex query in a pipeline that includes joins and/or transformation logic that alters the data from or pipeline from a query rather than stored procedure. I know that you can specify fields in a dataset, but don't know how to get around the "tablename" property.
If there is a way, what would that method be?
input is on-premises sql server. output is azure sql database.
UPDATED for clarity.
Yes, the sqlReaderQuery can be much more complex than what is provided in the examples, and it doesn't have to only use the Table Name in the Dataset.
In one of my pipelines, I have a Dataset with the TableName "dbo.tbl_Build", but my sqlReaderQuery looks at several tables in that database. Here's a heavily truncated example:
with BuildErrorNodes as (select infoNode.BuildId, ...) as MessageValue from dbo.tbl_BuildInformation2 as infoNode inner join dbo.tbl_BuildInformationType as infoType on (infoNode.PartitionId = infoType), BuildInfo as ...
It's a bit confusing to list a single table name in the Dataset, then use multiple tables in the query, but it works just fine.
There's a way to move data from on-premise SQL to Azure SQL using Data Factory.
You can use Copy Activity, check this code sample for your case specifically GitHub link to the ADF Activity source.
Basically you need create Copy Activity which will have TypeProperties with SqlSource and SqlSink sets look like this:
<!-- language: lang-json -->
"typeProperties": {
"source": {
"type": "SqlSource",
"SqlReaderQuery": "select * from [Source]"
},
"sink": {
"type": "SqlSink",
"WriteBatchSize": 1000000,
"WriteBatchTimeout": "00:05:00"
}
},
Also do mention - you can use not only selects from tables or views, but also [Table-Valued-Functions] will work as well.