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The following page has been changed by NamitJain: http://wiki.apache.org/hadoop/Hive/Roadmap ------------------------------------------------------------------------------ Before adding to the list below, please check [https://issues.apache.org/jira/browse/HADOOP/component/12312455 JIRA] to see if a ticket has already been opened for the feature. If not, please open a ticket on the [http://issues.apache.org/jira/browse/HADOOP Hadoop JIRA] and select "contrib/hive" as the component and also update the following list. - = 10/27/08 Roadmap Update = - - 1. Integrating Dynamic SerDe with the DDL. (Zheng/Pete) - This allows the users to create typed tables along with list and map types from the DDL - 2. Support for Statistics. (Ashish) - These stats are needed to make optimization decisions - 3. Join Optimizations. (Prasad) - Mapside joins, semi join techniques etc to do the join faster - 4. Predicate Pushdown Optimizations. (Namit) - pushing predicates just above the table scan for certain situations in joins as well as ensuring that only required columns are sent across map/reduce boundaries - 5. Group By Optimizations. (Joydeep) - various optimizations to make group by faster - 6. Optimizations to reduce the number of map files created by filter operations. (Dhrubha) - Filters with a large number of mappers produces a lot of files which slows down the following operations. This tries to address problems with that. - 7. Transformations in LOAD. (Joydeep) - LOAD currently does not transform the input data if it is not in the format expected by the destination table. - 8. Schemaless map/reduce. (Zheng) - TRANSFORM needs schema while map/reduce is schema less. - 9. Improvements to TRANSFORM. (Zheng) - Make this more intuitive to map/reduce developers - evaluate some other keywords etc.. - 10. Error Reporting Improvements. (Pete) - Make error reporting for parse errors better - 11. Help on CLI. (Joydeep) - add help to the CLI - 12. Explode and Collect Operators. (Zheng) - Explode and collect operators to convert collections to individual items and vice versa. - 13. Propagating sort properties to destination tables. (Prasad) - If the query produces sorted we want to capture that in the destination table's metadata so that downstream optimizations can be enabled. - - Other contributions from outside FB ... - 14. JDBC driver (Michi Mutsuzaki @ stanford.edu, Raghu @ stanford.edu) - 15. Fixes to CLI driver (Jeremy Huylebroeck) - 16. Web interface... = Roadmap/call to add more features = The following is the list of useful features that are on the Hive Roadmap: + * HAVING clause support + * Support for various statistical functions like Median, Standard Deviation, Variance etc. + * Support for Create Table as Select + * Support for views + * Support for Insert Appends + * Support for Inserts without listing the partitioning columns explicitly - the query should be able to derive that + * Support for Indexes + * Support for IN + * Support for Column Alias + * Support for Statistics. - These stats are needed to make optimization decisions + * Join Optimizations. - Mapside joins, semi join techniques etc to do the join faster + * Optimizations to reduce the number of map files created by filter operations. + * Transformations in LOAD. - LOAD currently does not transform the input data if it is not in the format expected by the destination table. + * Schemaless map/reduce. - TRANSFORM needs schema while map/reduce is schema less. + * Improvements to TRANSFORM. - Make this more intuitive to map/reduce developers - evaluate some other keywords etc.. + * Error Reporting Improvements. - Make error reporting for parse errors better + * Help on CLI. - add help to the CLI + * Explode and Collect Operators. - Explode and collect operators to convert collections to individual items and vice versa. + * Propagating sort properties to destination tables. - If the query produces sorted we want to capture that in the destination table's metadata so that downstream optimizations can be enabled. + * Propagating bucketing properties to destination tables. * Multiple group-by inserts * Generate multiple group-by results by scanning the source table only once * Example: @@ -39, +39 @@ * Let the user register UDF and UDAF * Expose register functions in UDFRegistry and UDAFRegistry * Provide commands in HiveCli to call those register functions - * JDBC driver + * ODBC/JDBC driver * Alter table * rename column * serde properties (delims, thrift classes)
