[jira] [Updated] (CALCITE-4994) SQL-to-RelNode conversion is slow if table contains hundreds of fields

["Jay Narale (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/CALCITE-4994?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Jay Narale updated CALCITE-4994:
--------------------------------
    Summary: SQL-to-RelNode conversion is slow if table contains hundreds of fields  (was: SqlToRelConverter creates FieldMap for every Identifier Instead of Memoizing it)

> SQL-to-RelNode conversion is slow if table contains hundreds of fields
> ----------------------------------------------------------------------
>
>                 Key: CALCITE-4994
>                 URL: https://issues.apache.org/jira/browse/CALCITE-4994
>             Project: Calcite
>          Issue Type: Improvement
>          Components: core
>            Reporter: Jay Narale
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 0.5h
>  Remaining Estimate: 0h
>
> When converting from Sql To Rel, In SqlToRelConverter for every single instance of an identifier we create a new map in 
> *_org.apache.calcite.sql2rel.SqlToRelConverter.Blackboard#lookupExp_*
>  
> {code:java}
> final Map<String, Integer> fieldOffsets = new HashMap<>();
> for (RelDataTypeField f : resolve.rowType().getFieldList()) {
> if (!fieldOffsets.containsKey(f.getName())) {
> fieldOffsets.put(f.getName(), f.getIndex());
> }
> }
> final Map<String, Integer> map = ImmutableMap.copyOf(fieldOffsets);{code}
>  
> So for a Sql Query
> {code:java}
> SELECT name, nation FROM customer{code}
> We would do the above operation twice.
> Memoization of this information will improve performance.
> In my database, I had observed that for a large table involving 1200 columns and a huge select having multiple expressions and operators, this part was a bottleneck.



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