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SQL Server 2019 Big Data Clusters Crash Course: Installing and Using a Big Data Cluster for Data Analysis / Woody, Buck.
- Format:
- Video
- Author/Creator:
- Woody, Buck, author.
- Language:
- English
- Subjects (All):
- Big data.
- Quantitative research--Computer programs.
- Quantitative research.
- Microsoft software.
- Genre:
- Electronic videos.
- Physical Description:
- 1 online resource (1 video file, approximately 1 hr., 3 min.)
- Edition:
- 1st edition
- Place of Publication:
- Apress, 2020.
- System Details:
- video file
- Summary:
- Learn the architecture and implementation of Microsoft’s latest SQL Server capability - Big Data Clusters. Combine SQL Server for data, PolyBase for data virtualization, Data Pools for scale-out data processing, and Spark with HDFS for scalable non-relational data processing and analysis. You’ll begin this video with a quick overview of the big data space, along with an easy-to-understand introduction to containers, Kubernetes, Spark, and HDFS. You’ll put those pieces together by planning and deploying your own cluster. Then it’s on to operationalizing the cluster through problem-solving with Transact-SQL, PolyBase, data processing at scale, and working with Spark and HDFS. What You Will Learn Understand big data technologies such as Spark and HDFS Deploy a Big Data Cluster on a Kubernetes environment in Azure Implement PolyBase queries to bring in data from external sources Run Transact-SQL statements and process relational data at scale Execute Spark jobs and machine learning from within SQL Server 2019 Implement basic security protocols to protect your data from theft Who This Video Is For Database professionals who are curious about SQL Server 2019’s flagship feature. For those who want to get started in querying and analyzing massive amounts of data using Spark and HDFS clusters while taking advantage of their SQL Server investment.
- Participant:
- Presenter: Buck Woody.
- Notes:
- Online resource; Title from title screen (viewed May 14, 2020)
- Title from resource description page (Safari, viewed September 30, 2020).
- OCLC:
- 1198249692
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