SQLBits 2014
Optimizing Temporal Queries
Writing efficient queries with temporal predicates is finally not a problem anymore.
Having a SQL Server solution for a problem does
not mean the job is done. Of course, the next immediate issue is the
performance. Temporal queries that involve intervals are typically very IO and
CPU intensive. For example, a test for overlapping intervals was solved with
inefficient queries for years. However, a handful of solutions with fast
queries was developed lately. This high-level technical session introduces five
different methods to get efficient queries that search for overlapping intervals.
Of course, these solutions can be implemented on other temporal problems as
well. Actually, the test for overlapping intervals is one of the most complex
temporal problems.
Speakers
Dejan Sarka's previous sessions
Statistical Analysis in T-SQL
Learn how to analyze your data with pure T-SQL to get the performance you cannot reach with R, Python, or other tools. Learn the math behind as well.
Data Overview and Manipulation - T-SQL, R, Python
Before doing any analysis, you have to prepare the data properly.
Temporal Data in SQL Server
Use temporal support in SQL Server and add what is missing out of the box.
Analysing Text with SQL Server 2014
This session introduces SQL Server 2012 and 2014 text mining capabilities.
Optimizing Temporal Queries
Writing efficient queries with temporal predicates is finally not a problem anymore.
Excel 2013 Analytics
Excel is “The” analytical tool in Microsoft suite for advanced analysts. This session introduces Excel 2013 and 2010 business intelligence capabilities.
A Deep Dive in SQL Server 2012 Data Warehousing
In this session, we are going to explain and test different DW features in SQL Server 2012, including star join optimization through bitmap filters, table partitioning, window functions, columnstore indices and more.