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45 lines
2.5 KiB
Markdown
45 lines
2.5 KiB
Markdown
# SQL Server big data clusters
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## Pre-requisites
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1. Kubernetes cluster configuration & Kubectl command-line utility
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2. Curl utility
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3. Sqlcmd utility
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4. Bcp utility
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5. Azure Data Studio or SQL Server Management Studio
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6. SQL Server 2019 big data cluster
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Installation instructions for SQL Server 2019 big data cluster can be found [here](https://docs.microsoft.com/en-us/sql/big-data-cluster/deployment-guidance?view=sql-server-2017).
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## Samples Setup
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**Before you begin**, download the sample database [backup file](https://sqlchoice.blob.core.windows.net/sqlchoice/static/tpcxbb_1gb.bak) and save it locally. Run the CMD script called *bootstrap-sample-db.cmd* or the shell script *bootstrap-sample-db.sh* depending on your platform. This script will restore the database on the SQL Master instance, execute the *bootstrap-sample-db.sql* script, create the database objects needed, export the web_clickstreams & inventory tables to CSV file, and upload the web_clickstreams CSV file to HDFS inside the SQL Server 2019 big data cluster.
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__[data-pool](data-pool/)__
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### Data ingestion using Spark
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Connect to the master instance in your SQL Server big data cluster and the SQL Server big data cluster endpoint, and follow the steps in *data-pool/data-ingestion-spark.sql*.
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### Data ingestion using sql
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Connect to the master instance in your SQL Server big data cluster and execute the steps in *data-pool/data-ingestion-sql.sql*.
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__[data-virtualization](data-virtualization/)__
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### External table over HDFS
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Connect to the master instance in your SQL Server big data cluster and execute the steps in *data-virtualization/external-table-hdfs.sql*.
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### External table over Oracle
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To execute this sample script, you will need following:
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1. Oracle instance and credentials
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1. Create inventory table in Oracle using [data-virtualization/inventory-oracle.sql](data-virtualization/inventory-oracle.sql/) script
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1. Import the inventory.csv file generated by the bootstrap-sample-db script to a table in Oracle
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Connect to the master instance in your SQL Server big data cluster and execute the steps in *data-virtualization/external-table-oracle.sql*.
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__[machine-learning](machine-learning/)__
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### SQL Server ML Services on master instance
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Connect to the master instance in your SQL Server big data cluster and execute the steps in *machine-learning/sql/book-category-r-ml.sql*.
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### Spark ML
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Connect to the SQL Server big data cluster endpoint, and run the notebook files *machine-learning/spark/1-data-prep.ipynb* and *machine-learning/spark/2-build-ml-model.ipynb* cell by cell.
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