Azure SQL DW – Elastic Data Analytics in the cloud Josh Sivey | Microsoft TSP #492 | Phoenix.

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Presentation transcript:

Azure SQL DW – Elastic Data Analytics in the cloud Josh Sivey | Microsoft TSP #492 | Phoenix

Agenda What is Azure SQL Data Warehouse? Technical and Architecture Details Demos! SQL SATURDAY | #492 | PHOENIX 2016

What is Azure SQL Data Warehouse? Azure SQL Data Warehouse is a cloud- based, scale-out database capable of processing massive volumes of data Both relational and non-relational. Built on massively parallel processing (MPP) architecture Platform-as-a-service model SQL SATURDAY | #492 | PHOENIX 2016

What is Azure SQL Data Warehouse? Increase, decrease, pause, or resume compute in seconds. Leverages the Azure platform. It's easy to deploy, seamlessly maintained. Fully fault tolerant with automatic back-ups. Develop with familiar SQL Server T-SQL and tools. SQL SATURDAY | #492 | PHOENIX 2016

What is Azure SQL Data Warehouse? By combining MPP architecture and Azure storage capabilities, SQL Data Warehouse can: Grow or shrink storage independent of compute. Grow or shrink compute without moving data. Pause compute capacity while keeping data intact. Resume compute capacity at a moment's notice. SQL SATURDAY | #492 | PHOENIX 2016

Architecture SQL SATURDAY | #492 | PHOENIX 2016

Data Warehouse Units (DWUs) Compute usage in SQL Data Warehouse is measured using SQL Data Warehouse Units (DWUs). DWUs are a measure of underlying power that your data warehouse has, and are designed to ensure that you have a standard amount of performance associated with your warehouse at any given time. SQL SATURDAY | #492 | PHOENIX 2016

Development and Design Considerations Concurrent Queries and Concurrency Slots 32 concurrent queries, slots depend on DWUs SQL DW exposes four different resource classes in the form of database roles smallrc, mediumrc, largerc, xlargerc Resource classes are an essential part of SQL DW workload management. They govern the computational resources allocated to the query. SQL SATURDAY | #492 | PHOENIX 2016

Distribution of Data Options - Hash vs. Round Robin It affects query performance Minimize data movement Avoid data skew Provide balanced execution SQL SATURDAY | #492 | PHOENIX 2016

Distribution of Data - Hash Hash function applied to a column “co-locating” data across a distribution speeds up joins on the key and aggregations SQL SATURDAY | #492 | PHOENIX 2016

Distribution of Data – Round Robin Non-deterministic distribution Common dimension tables Tables that don’t distribute evenly SQL SATURDAY | #492 | PHOENIX 2016

Data Loading You can load data into Azure SQL DW via: PolyBase (CTAS) Azure Data Factory BCP command line utility SSIS 3 rd party data loading tools SQL SATURDAY | #492 | PHOENIX 2016

Integration Azure SQL DW integrates with Power BI Azure Data Factory Azure Machine Learning Azure Stream Analytics SQL SATURDAY | #492 | PHOENIX 2016

Demos Provision a Azure SQL Data Warehouse Use PolyBase to query non-relational data Sample query plan reviews Auditing and Threat Detection SQL SATURDAY | #492 | PHOENIX 2016

Resources What is Azure SQL Data Warehouse? us/documentation/articles/sql-data-warehouse- overview-what-is/ us/documentation/articles/sql-data-warehouse- overview-what-is/ Choosing hash distributed table vs. round- robin distributed table in Azure SQL DW Service 11/choosing-hash-distributed-table-vs-round- robin-distributed-table-in-azure-sql-dw-service/ 11/choosing-hash-distributed-table-vs-round- robin-distributed-table-in-azure-sql-dw-service/ SQL SATURDAY | #492 | PHOENIX 2016

Questions and Contact Information Linked In SQL SATURDAY | #492 | PHOENIX 2016

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