SQL Knowledge Bank - Azure

  Introduction As we are discussing about the power of Vertipaq Engine, in this post we are going to discuss about another beautiful technique that Vertipaq Engine maintain to make our query faster and that is Column Elimination and Segment Elimination.   Hope it will be interesting. Case Study We have a table which is imported into Vertipaq engine. Table Name: Order_Details   Column Elimination As Vertipaq Engine stores data as a columner fashion so it’s looks like.   Now we need to fetch data for Customer ‘ABC Company’ and want to know the Total Quntity the specified company purchased. For that we need only columns named Customer and Qty. All others columns are simply eliminated. It actually limit the data by eleminating the columns and called columns elemenation. Segment Elimination This is done by horizontal Partitioning.   For Power Pivot it takes 1 million per partition and for SSAS Tabular it takes 8 million per Partition. Now how it works.

  Introduction   In our previous post, we are discussing about Vertipaq Data compression one of the best feature of Vertipaq engine by Microsoft. In this post we are trying to discuss about Vertipaq Columnar Database. The ultimate feature of Vertipaq engine is to speed up the query performance. Hope it will be interesting.   What the Special in Vertipaq Engine Vertipaq is an in-memory columnar database. Being in-memory means that all of the data handled by a model reside in RAM.   How Database works with a Table To understand the columnar database we have to understand, how data is retrieved from a table in our traditional database like MS SQL Server. Let’s take an example of a table. Table Name: tbl_OrderDetails The data in a Database table stores in 8 KB page named data page. The 8 data page combined together to from an Extinct. When we search for a specified product to understand how many Quantity has been s

Introduction Microsoft introduces a very powerful engine for fast query named Vertipaq . Which is used in the Power BI and SSAS Tabular model? Here we are not going to discuss about Power BI or SSIS Tabular model. Our main concern is to identify how the Vertipaq Engine works and how it provide Fastest Query. The Vertipaq Engine stores the table in a columnar format and established relation between columns. In this blog post we are going to discuss about Data Compression mechanism and try to explain it.   Case Study We have a table which is imported into Vertipaq engine. Table Name:  Order_Details     How Vertipaq works on this Table Vertipaq Compress Text in a Table Text takes lot of space in data base. So Vertipaq need to compress it. It maintain another table with distinct Text value and Id number like this. It is also called Dictionary/ Hash compression.   Product_ID_Dictionary              Value Encoding Here Vertipaq tries to convert Value into One Digit where as possible. TO u