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Jitendra Nath Pandey commented on HIVE-4160: -------------------------------------------- This will be an incremental work in multiple phases with no regression on current system. We will publish a design/scope document very soon. The main idea behind the proposal is to transform the execution engine to process a row batch at a time instead of a single row. The row batch will consist of column vectors and each operator will process the whole column vector at a time. The column vector will consist of array(s) of primitive types as far as possible. The expressions will be implemented for various data types using pre-compiled templates. The appropriate expressions will be added to the operators based on data types. A vectorized iterator interface will be implemented by the file formats to provide vectorized input to the operator tree. > Vectorized Query Execution in Hive > ---------------------------------- > > Key: HIVE-4160 > URL: https://issues.apache.org/jira/browse/HIVE-4160 > Project: Hive > Issue Type: New Feature > Reporter: Jitendra Nath Pandey > Assignee: Jitendra Nath Pandey > > Hive query execution engine currently processes one row at a time. A single > row of data goes through all the operators before next row can be processed. > This mode of processing is very inefficient in terms of CPU usage. Research > has demonstrated that this yields very low instructions per cycle [MonetDB]. > Also currently hive heavily relies on lazy deserialization and data columns > go through a layer of object inspectors that identify column type, > de-serialize data and determine appropriate expression routines in the inner > loop. These layers of virtual method calls further slow down the processing. > Reference: http://www-db.cs.wisc.edu/cidr/cidr2005/papers/P19.pdf -- This message is automatically generated by JIRA. If you think it was sent incorrectly, please contact your JIRA administrators For more information on JIRA, see: http://www.atlassian.com/software/jira