i setup the VPN connection between my on-prem sql server and GCP. i need to load more than 10 million rows data from sql server to bigquery. is there any way to achieve it? can i use SSIS to load the data to bigquery?
my team lead request to use dataflow to load the data to bigquery and not using SSIS.
In regards to using SSIS to load the data from the on-premises SQL Server to BigQuery, this might be what you're looking for. As for using Cloud Dataflow, the official GCP documentation details how it can be done, although you might need to use Cloud Storage as an intermediate data sink.
Related
We have a requirement to move data from oracle Cloud storage to Azure Cloud storage.
The requirement is basically to move data from an Oracle ADW database (hosted on Oracle cloud) to Snowflake database (hosted on Azure).
Since the data volume in tables is huge (some with 60mil+ records) we do not wish to use any ETL tool and instead want to setup a pipeline as below.
Oracle ADW database -> Store data in Oracle storage --> Move data to Azure Cloud storage -> Load into Snowflake using snowpipe or similar snowflake utilities.
How should I go about this implementation?
Also share your views on whether we can use Oracle fastconnect and Azure ExpressRoute to directly pull data from Oracle Cloud onto snowflake (or into Azure storage)
I am looking for the same thing with the simplest method from Oracle (on prem but could be cloud), into Snowflake. Looks like data must be exporeted or dropped to external tables, shifted to Azure Blob storage (like AWS S3), then pushed into Snowflake using COPY INTO - basically copying on disk external tables. This is what Snowpipe does:
"Snowpipe copies the files into a queue, from which they are loaded into the target table in a continuous, serverless fashion based on parameters defined in a specified pipe object. The following table indicates the cloud storage service support for automated Snowpipe from Snowflake accounts hosted on each cloud platform:"
It's been a while since I have worked with this. The other option is GoldenGate, which was not expensive the last time I looked into it:
https://www.snowflake.com/blog/continuous-data-replication-into-snowflake-with-oracle-goldengate/
Easy, simple, fast. Anyone have any better ideas would be appreciated.
There is an option to connect a Cloud mySQL instance from BigQuery. I just wanted to know how we can connect a Cloud SQL Server instance to BigQuery.
SQL Server:
There are a bunch of third-party extensions/tools that provide this service. One of them is SSIS Data Flow Source & Destination for Google BigQuery, which is Visual Studio extension that connects SQL Server with Google BigQuery data through SSIS Workflows.:
https://www.cdata.com/drivers/bigquery/ssis/
https://marketplace.visualstudio.com/items?itemName=CDATASOFTWARE.SSISDataFlowSourceDestinationforGoogleBigQuery
In regards to using SQL Server Integration Services to load the data from the on-premises SQL Server to BigQuery, you can take a look for this site. You can also perform ETL from a relational database into BigQuery using Cloud Dataflow, the official documentation details how it can be done, you might need to use Cloud Storage as an intermediate data sink.
Cloud SQL:
BigQuery allows to query data from Cloud SQL by using federated query. The connection must be created within the same project where your Cloud SQL instance is located. If you want to query your data stored in your Cloud SQL instance from BigQuery located in another project, please follow the steps listed below:
Enable the BigQuery API and the BigQuery connection API within your project.
Create a connection to your Cloud SQL instance within the project by following this documentation.
Once you have created the connection, please locate and select it within BigQuery.
Click on the SHARE CONNECTION button and grant permissions to the users that will be use that connection. Please note that the BigQuery Connection User role is the only needed to use a shared connection.
Additionally, please notice that the "Cloud SQL federated queries" feature is in a Beta stage and might change or have limited support (is no available for certain regions, in which case, it is required to use one the supported options mentioned here). Please remember, that to use Cloud SQL Federated queries in BigQuery, the intances need to have a public IP.
If you are limited e.g. by region, one good option might be exporting the data from CloudSQL to Storage as a CSV, and then load it into BigQuery. If you need, it is possible to automate this process using Cloud Composer, refer to this article.
Other approach is to extract information from Cloud SQL (with exports) and import it into BigQuery through load jobs, or streaming inserts.
I hope you find the above pieces of information useful.
It is possible, but be warned the feature is currently Beta
https://cloud.google.com/bigquery/docs/cloud-sql-federated-queries
I need to export a multi terabyte dataset processed via Azure Data Lake Analytics(ADLA) onto a SQL Server database.
Based on my research so far, I know that I can write the result of (ADLA) output to a Data Lake store or WASB using built-in outputters, and then read the output data from SQL server using Polybase.
However, creating the result of ADLA processing as an ADLA table seems pretty enticing to us. It is a clean solution (no files to manage), multiple readers, built-in partitioning, distribution keys and the potential for allowing other processes to access the tables.
If we use ADLA tables, can I access ADLA tables via SQL Polybase? If not, is there any way to access the files underlying the ADLA tables directly from Polybase?
I know that I can probably do this using ADF, but at this point I want to avoid ADF to the extent possible - to minimize costs, and to keep the process simple.
Unfortunately, Polybase support for ADLA Tables is still on the roadmap and not yet available. Please file a feature request through the SQL Data Warehouse User voice page.
The suggested work-around is to produce the information as Csv in ADLA and then create the partitioned and distributed table in SQL DW and use Polybase to read the data and fill the SQL DW managed table.
I need to setup a data pipeline from some source databases like Oracle, MySQL and load the data to BigQuery.
How can I use google-cloud-dataflow to read data from a database(jdbc connection) and write to BigQuery tables using Python.
Also, I have some hive tables in an on-premise Hadoop cluster, how do I transfer this data to BigQuery.
I couldn't find the right documentation or examples to achieve this.
Can you please point me in the right direction.
I applied a solution in my project to provide such thing, you need to follow these steps:
Load data from Google Cloud SQL to Google Cloud storage in CSV by following this link.
Load the CSV data from Google cloud storage directly into BigQuery by following this link.
Is there a way to output U-SQL results directly to a SQL DB such as Azure SQL DB? Couldn't find much about that.
Thanks!
U-SQL only currently outputs to files or internal tables (ie tables within ADLA databases), but you have a couple of options. Azure SQL Database has recently gained the ability to load files from Azure Blob Storage using either BULK INSERT or OPENROWSET, so you could try that. This article shows the syntax and gives a reminder that:
Azure Blob storage containers with public blobs or public containers
access permissions are not currently supported.
wasb://<BlobContainerName>#<StorageAccountName>.blob.core.windows.net/yourFolder/yourFile.txt
BULK INSERT and OPENROWSET with Azure Blob Storage is shown here:
https://blogs.msdn.microsoft.com/sqlserverstorageengine/2017/02/23/loading-files-from-azure-blob-storage-into-azure-sql-database/
You could also use Azure Data Factory (ADF). Its Copy Activity could load the data from Azure Data Lake Storage (ADLS) to an Azure SQL Database in two steps:
execute U-SQL script which creates output files in ADLS (internal tables are not currently supported as a source in ADF)
move the data from ADLS to Azure SQL Database
As a final option, if your data is likely to get into larger volumes (ie Terabytes (TB) then you could use Azure SQL Data Warehouse which supports Polybase. Polybase now supports both Azure Blob Storage and ADLS as a source.
Perhaps if you can tell us a bit more about your process we can refine which of these options is most suitable for you.