My problem statement is that I have a csv blob and I need to import that blob into a sql table. Is there an utility to do that?
I was thinking of one approach, that first to copy blob to on-premise sql server using AzCopy utility and then import that file in sql table using bcp utility. Is this the right approach? and I am looking for 1-step solution to copy blob to sql table.
Regarding your question about the availability of a utility which will import data from blob storage to a SQL Server, AFAIK there's none. You would need to write one.
Your approach seems OK to me. Though you may want to write a batch file or something like that to automate the whole process. In this batch file, you would first download the file on your computer and the run the BCP utility to import the CSV in SQL Server. Other alternatives to writing batch file are:
Do this thing completely in PowerShell.
Write some C# code which makes use of storage client library to download the blob and once the blob is downloaded, start the BCP process in your code.
To pull a blob file into an Azure SQL Server, you can use this example syntax (this actually works, I use it):
BULK INSERT MyTable
FROM 'container/folder/folder/file'
WITH ( DATA_SOURCE = 'ds_blob',BATCHSIZE=10000,FIRSTROW=2);
MyTable has to have identical columns (or it can be a view against a table that yields identical columns)
In this example, ds_blob is an external data source which needs to be created beforehand (https://learn.microsoft.com/en-us/sql/t-sql/statements/create-external-data-source-transact-sql)
The external data source needs to use a database contained credential, which uses an SAS key which you need to generate beforehand from blob storage https://learn.microsoft.com/en-us/sql/t-sql/statements/create-database-scoped-credential-transact-sql)
The only downside to this mehod is that you have to know the filename beforehand - there's no way to enumerate them from inside SQL Server.
I get around this by running powershell inside Azure Automation that enumerates blobds and writes them into a queue table beforehand
Related
I have a pipeline that creates a dataset from a stored procedure on Azure SQL Server.
I want to then manipulate it in a power query step within the factory, but it fails to load in the power query editor with this error.
It opens up the JSON file (to correct it, I assume) but I can't see anything wrong with it.
If I download the extract from blob and upload it again as a .csv then it works fine.
The only difference I can find is that if I upload a blob direct to storage then the file information for the blob looks like this:
If I just let ADF create the .csv in blob storage the file info looks like this:
So my assumption is that somewhere in the process in ADF that creates the .csv file it's getting something wrong, and the Power Query module can't recognise it as a valid file.
All the other parts of the pipeline (Data Flows, other datasets) recognise it fine, and the 'preview data' brings it up correctly. It's just PQ that won't read it.
Any thooughts? TIA
I reproduced the same. When data is copied from SQL database to BLOB as csv file, Power query is unable to read. Also, Power query doesn't support json file. But when I tried to download the csv file and reupload, it worked.
Below are the steps to overcome this issue.
When I tried to upload the file in Blob and create the dataset for that file in power query, Schema is imported from connection/Store. It forces us to import schema either from connection/store or from sample file. There is no option as none here.
When data is copied from sql db to Azure blob, and dataset which uses the blob storage didn't have schema imported by default.
Once imported the schema, power query activity ran successfully.
Output before importing schema in dataset
After importing schema in dataset
I am trying to import a small table of data from Azure SQL into Snowflake using Azure Data Factory.
Normally I do not have any issues using this approach:
https://learn.microsoft.com/en-us/azure/data-factory/connector-snowflake?tabs=data-factory#staged-copy-to-snowflake
But now I have an issue, with a source table that looks like this:
There is two columns SLA_Processing_start_time and SLA_Processing_end_time that have the datatype TIME
Somehow, while writing the data to the staged area, the data is changed to something like 0:08:00:00.0000000,0:17:00:00.0000000 and that causes for an error like:
Time '0:08:00:00.0000000' is not recognized File
The mapping looks like this:
I have tried adding a TIME_FORMAT property like 'HH24:MI:SS.FF' but that did not help.
Any ideas to why 08:00:00 becomes 0:08:00:00.0000000 and how to avoid it?
Finally, I was able to recreate your case in my environment.
I have the same error, a leading zero appears ahead of time (0: 08:00:00.0000000).
I even grabbed the files it creates on BlobStorage and the zeros are already there.
This activity creates CSV text files without any error handling (double quotes, escape characters etc.).
And on the Snowflake side, it creates a temporary Stage and loads these files.
Unfortunately, it does not clean up after itself and leaves empty directories on BlobStorage. Additionally, you can't use ADLS Gen2. :(
This connector in ADF is not very good, I even had problems to use it for AWS environment, I had to set up a Snowflake account in Azure.
I've tried a few workarounds, and it seems you have two options:
Simple solution:
Change the data type on both sides to DateTime and then transform this attribute on the Snowflake side. If you cannot change the type on the source side, you can just use the "query" option and write SELECT using the CAST / CONVERT function.
Recommended solution:
Use the Copy data activity to insert your data on BlobStorage / ADLS (this activity did it anyway) preferably in the parquet file format and a self-designed structure (Best practices for using Azure Data Lake Storage).
Create a permanent Snowflake Stage for your BlobStorage / ADLS.
Add a Lookup activity and do the loading of data into a table from files there, you can use a regular query or write a stored procedure and call it.
Thanks to this, you will have more control over what is happening and you will build a DataLake solution for your organization.
My own solution is pretty close to the accepted answer, but I still believe that there is a bug in the build-in direct to Snowflake copy feature.
Since I could not figure out, how to control that intermediate blob file, that is created on a direct to Snowflake copy, I ended up writing a plain file into the blob storage, and reading it again, to load into Snowflake
So instead having it all in one step, I manually split it up in two actions
One action that takes the data from the AzureSQL and saves it as a plain text file on the blob storage
And then the second action, that reads the file, and loads it into Snowflake.
This works, and is supposed to be basically the same thing the direct copy to Snowflake does, hence the bug assumption.
I have a table in SQL Server where I need to insert data on regular base. Each day I perform same task importing data manually, it makes me feel tedious so I need your help. Is it possible to send data from CSV file to SQL Server's existing table without doing manual procedure.
Or using python to create a scrip that send data from CSV file to SQL Server at fixed time automatically.
First you have to create a python script that inserts data into SQL server after reading CSV file. Then you should create a CRON job on your server that runs this script regularly. This might be a possible solution for your problem.
I am loading 50GB CSV file From Azure Blob to Azure SQL DB using OPENROWSET.
It takes 7 hours to load this file.
Can you please help me with possible ways to reduce this time?
The easiest option IMHO is just use BULK INSERT. Move the csv file into a Blob Store and the import it directly using BULK INSERT from Azure SQL. Make sure Azure Blob storage and Azure SQL are in the same Azure region.
To make it as fast as possible:
split the CSV in more than one file (for example using something like a CSV splitter. This looks nice https://www.erdconcepts.com/dbtoolbox.html. Never tried and just came up with a simple search, but looks good)
run more BULK INSERT in parallel using TABLOCK option. (https://learn.microsoft.com/en-us/sql/t-sql/statements/bulk-insert-transact-sql?view=sql-server-2017#arguments). This, if the target table is empty, will allow multiple concurrent bulk operations in parallel.
make sure you are using an higher SKU for the duration of the operation. Depending on the SLO (Service Level Objective) you're using (S4? P1, vCore?) you will get a different amount of log throughput, up to close 100 MB/Sec. That's the maximum speed you can actually achieve. (https://learn.microsoft.com/en-us/azure/sql-database/sql-database-resource-limits-database-server)
Please try using Azure Data Factory.
First create the destination table on Azure SQL Database, let's call it USDJPY. After that upload the CSV to an Azure Storage Account. Now create your Azure Data Factory instance and choose Copy Data.
Next, choose "Run once now" to copy your CSV files.
Choose "Azure Blob Storage" as your "source data store", specify your Azure Storage which you stored CSV files.
Provide information about Azure Storage account.
Choose your CSV files from your Azure Storage.
Choose "Comma" as your CSV files delimiter and input "Skip line count" number if your CSV file has headers
Choose "Azure SQL Database" as your "destination data store".
Type your Azure SQL Database information.
Select your table from your SQL Database instance.
Verify the data mapping.
Execute data copy from CSV files to SQL Database just confirming next wizards.
I am a C# developer, I am not really good with SQL. I have a simple questions here. I need to move more than 50 millions records from a database to other database. I tried to use the import function in ms SQL, however it got stuck because the log was full (I got an error message The transaction log for database 'mydatabase' is full due to 'LOG_BACKUP'). The database recovery model was set to simple. My friend said that importing millions records using task->import data will cause the log to be massive and told me to use loop instead to transfer the data, does anyone know how and why? thanks in advance
If you are moving the entire database, use backup and restore, it will be the quickest and easiest.
http://technet.microsoft.com/en-us/library/ms187048.aspx
If you are just moving a single table read about and use the BCP command line tools for this many records:
The bcp utility bulk copies data between an instance of Microsoft SQL Server and a data file in a user-specified format. The bcp utility can be used to import large numbers of new rows into SQL Server tables or to export data out of tables into data files. Except when used with the queryout option, the utility requires no knowledge of Transact-SQL. To import data into a table, you must either use a format file created for that table or understand the structure of the table and the types of data that are valid for its columns.
http://technet.microsoft.com/en-us/library/ms162802.aspx
The fastest and probably most reliable way is to bulk copy the data out via SQL Server's bcp.exe utility. If the schema on the destination database is exactly identical to that on the source database, including nullability of columns, export it in "native format":
http://technet.microsoft.com/en-us/library/ms191232.aspx
http://technet.microsoft.com/en-us/library/ms189941.aspx
If the schema differs between source and target, you will encounter...interesting (yes, interesting is a good word for it) problems.
If the schemas differ or you need to perform any transforms on the data, consider using text format. Or another format (BCP lets you create and use a format file to specify the format of the data for export/import).
You might consider exporting data in chunks: if you encounter problems it gives you an easier time of restarting without losing all the work done so far.
You might also consider zipping the exported data files up to minimize time on the wire.
Then FTP the files over to the destination server.
bcp them in. You can use the bcp utility on the destination server for the BULK IMPORT statement in SQL Server to do the work. Makes no real difference.
The nice thing about using BCP to load the data is that the load is what is described as a 'non-logged' transaction, though it's really more like a 'minimally logged' transaction.
If the tables on the destination server have IDENTITY columns, you'll need to use SET IDENTITY statement to disable the identity column on the the table(s) involved for the nonce (don't forget to reenable it). After your data is imported, you'll need to run DBCC CHECKIDENT to get things back in synch.
And depending on what your doing, it can sometimes be helpful to put the database in single-user mode or dbo-only mode for the duration of the surgery: http://msdn.microsoft.com/en-us/library/bb522682.aspx
Another approach I've used to great effect is to use Perl's DBI/DBD modules (which provide access to the bulk copy interface) and write a perl script to suck out the data from the source server, transform it and bulk load it directly into the destination server, without having to save it to disk and move it. Also means you can trap errors and design things for recovery and restart right at the point of failure.
Use BCP to migrate data.
Another approach i have used in the past is to take a backup of the transaction log and shrink the log Prior to the migration. Split the migration script in parts and run the log backup- shrink - migrate iteration a few times.