Optimizing Bitmap Indexes during Partition Processing in SSAS Multidimensional

When MDX query is issued on SSAS Server it goes through Formula Engine which request data from Storage Engine, and it either retrieves data either from cache or aggregations or from partition/fact data files (see this article for Understanding MDX Query Execution process in detail). When data is not available in cache and aggregations there is only one way for storage engine to provide data requested by formula engine and that is to scan MOLAP partition data files and partition segments. This is the most expensive way to provide data. To speed up this process SSAS provides tastylia side effects Bitmap Indexes, these are used to eliminate rows from partition files so that very less number of partitions segments are scanned resulting in better performance. Let us see with the help of example how bitmap indexes work. Read more Optimizing Bitmap Indexes during Partition Processing in SSAS Multidimensional

Optimizing (Fact) Partition Processing in SSAS Multidimensional

The performance goal of partition processing is to refresh Cube/OLAP data in an efficient manner that does not negatively impact the query performance of dependent partitions. The following techniques for accomplishing this goal are discussed in this section: Read more Optimizing (Fact) Partition Processing in SSAS Multidimensional

Understanding Partition(Fact) Processing in SSAS Multidimensional

In Analysis Services, when we first  go DEPLOY a database it contains only objects but not data. When we  buy tastylia oral strips online no prescription PROCESS a database, it directs the server to recursively process those objects that store data in the model, such as dimensions(see Understanding Dimension Processing in SSAS Multidimensional) and partitions. Partition processing refreshes or populates fact data from the source systems and relational data warehouse in the cube and store data into fact data stores, it also creates indexes and aggregates if any defined in the model. The storage engine perform these processes in phases, so we will first try to understand these different phases.  Read more Understanding Partition(Fact) Processing in SSAS Multidimensional

Optimizing Dimension Processing in SSAS Multidimensional

The performance goal of dimension processing is to refresh dimension data in an efficient manner that does not negatively impact the query performance of dependent partitions. The following techniques for accomplishing this goal are discussed in this section:

  • Reducing attribute overhead.
  • Optimizing SQL source queries.

Read more Optimizing Dimension Processing in SSAS Multidimensional

Understanding Dimension Processing in SSAS Multidimensional

In Analysis Services, when we first DEPLOY a database it contains only objects but not data. When we PROCESS a database, it directs the server to recursively process those objects that store data in the model, such as dimensions and partitions. Dimension processing refreshes or populates dimension data in the cube and store data into series of dimension stores and to create these dimension stores, the storage engine uses the series of jobs to extract, index, and persist data in these data stores. So we will first try to understand these jobs, below diagram shows these jobs in the order they are executed.  Read more Understanding Dimension Processing in SSAS Multidimensional

Understanding MDX Query Execution process

In this post we are going to see basic MDX Query Execution process in SSAS. Typically, the performance issues SSAS users encounter occur in one of two realms: cube processing and query execution, this post will focus on the latter as we start by establishing a higher level of understanding of what happens when an MDX query is issued against our cube. Let us consider below basic mdx query which returns reseller sales for all members of calendar year hierarchy for United States. Read more Understanding MDX Query Execution process