Performance tuning in Qlik View:
Number of rows & columns: we should be selective about what fields are to be included in the qlikview document and eliminate those fields which are currently not in used. We can load five years of data in QV instead of loading 10 years of data.
Number of Distinct Values: Fields with distinct values use the most space. Using count(distinct) forces QV to switch from using multicore to use only one core. Time stamps with mins or seconds can be truncated to store only date thus reducing the processing time.
Data Model: Qlik View can analyze multiple data sources but works most efficiently with Star Schema or Snow flake Schema, The Star Schema Consists of few fact tables possibly only one ,referencing any no. of dimension tables
User Interfaces: Resource intensive expression like count(distinct) if() should be avoided. Set analysis should be used instead. Complex script should be done in script
rather than in charts/tables. Macros should be replaced by built in QV functions. Expressions which are used frequently in more than one chart/table should be stored in a variable which reduces the calculation time. Minimize the chart objects which are less important as chart expressions in minimized objects are not calculated.
Number of rows & columns: we should be selective about what fields are to be included in the qlikview document and eliminate those fields which are currently not in used. We can load five years of data in QV instead of loading 10 years of data.
Number of Distinct Values: Fields with distinct values use the most space. Using count(distinct) forces QV to switch from using multicore to use only one core. Time stamps with mins or seconds can be truncated to store only date thus reducing the processing time.
Data Model: Qlik View can analyze multiple data sources but works most efficiently with Star Schema or Snow flake Schema, The Star Schema Consists of few fact tables possibly only one ,referencing any no. of dimension tables
User Interfaces: Resource intensive expression like count(distinct) if() should be avoided. Set analysis should be used instead. Complex script should be done in script
rather than in charts/tables. Macros should be replaced by built in QV functions. Expressions which are used frequently in more than one chart/table should be stored in a variable which reduces the calculation time. Minimize the chart objects which are less important as chart expressions in minimized objects are not calculated.
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