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60 lines
3.8 KiB
Markdown
60 lines
3.8 KiB
Markdown
# SQL Server big data clusters
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Installation instructions for SQL Server 2019 big data clusters can be found [here](https://docs.microsoft.com/en-us/sql/big-data-cluster/deployment-guidance?view=sql-server-ver15).
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## Samples Setup
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**Before you begin**, load the sample data into your big data cluster. For instructions, see [Load sample data into a SQL Server 2019 big data cluster](https://docs.microsoft.com/en-us/sql/big-data-cluster/tutorial-load-sample-data).
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## Executing the sample scripts
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The scripts should be executed in a specific order to test the various features. Execute the scripts from each folder in below order:
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1. __[spark/data-loading/transform-csv-files.ipynb](spark/data-loading/transform-csv-files.ipynb)__
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1. __[data-virtualization/generic-odbc](data-virtualization/generic-odbc)__
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1. __[data-virtualization/hadoop](data-virtualization/hadoop)__
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1. __[data-virtualization/storage-pool](data-virtualization/storage-pool)__
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1. __[data-virtualization/oracle](data-virtualization/oracle)__
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1. __[data-pool](data-pool/)__
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1. __[machine-learning/sql/r](machine-learning/sql/r)__
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1. __[machine-learning/sql/python](machine-learning/sql/python)__
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## __[data-pool](data-pool/)__
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SQL Server 2019 big data cluster contains a data pool which consists of many SQL Server instances to store data & query in a scale-out manner.
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### Data ingestion using Spark
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The sample script [data-pool/data-ingestion-spark.sql](data-pool/data-ingestion-spark.sql) shows how to perform data ingestion from Spark into data pool table(s).
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### Data ingestion using sql
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The sample script [data-pool/data-ingestion-sql.sql](data-pool/data-ingestion-sql.sql) shows how to perform data ingestion from T-SQL into data pool table(s).
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## __[data-virtualization](data-virtualization/)__
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SQL Server 2019 or SQL Server 2019 big data cluster can use PolyBase external tables to connect to other data sources.
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### External table over Generic ODBC data source
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The [data-virtualization/generic-odbc](data-virtualization/generic-odbc) folder contains samples that demonstrate how to query data in MySQL & PostgreSQL using external tables and generic ODBC data source. The generic ODBC data soruce can be used only in SQL Server 2019 on Windows.
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### External table over Hadoop
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The [data-virtualization/hadoop](data-virtualization/hadoop) folder contains samples that demonstrate how to query data in HDFS using external tables. This demonstrates the functionality available from SQL Server 2016 using the HADOOP data source.
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### External table over Oracle
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The [data-virtualization/oracle](data-virtualization/oracle) folder contains samples that demonstrate how to query data in Oracle using external tables.
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### External table over Storage Pool
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SQL Server 2019 big data cluster contains a storage pool consisting of HDFS, Spark and SQL Server instances. The [data-virtualization/storage-pool](data-virtualization/storage-pool) folder contains samples that demonstrate how to query data in HDFS inside SQL Server 2019 big data cluster.
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## __[deployment](deployment/)__
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The [deployment](deployment) folder contains the scripts for deploying a Kubernetes cluster for SQL Server 2019 big data cluster.
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## __[machine-learning](machine-learning/)__
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SQL Server 2016 added support executing R scripts from T-SQL. SQL Server 2017 added support for executing Python scripts from T-SQL. SQL Server 2019 adds support for executing Java code from T-SQL. SQL Server 2019 big data cluster adds support for executing Spark code inside the big data cluster.
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### SQL Server Machine Learning Services
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The [machine-learning\sql](machine-learning\sql) folder contains the sample SQL scripts that show how to invoke R, Python, and Java code from T-SQL.
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### Spark Machine Learning
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The [machine-learning\spark](machine-learning\spark) folder contains the Spark samples.
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