Github user dyozie commented on a diff in the pull request:
https://github.com/apache/incubator-hawq-docs/pull/45#discussion_r85779030
--- Diff: bestpractices/querying_data_bestpractices.html.md.erb ---
@@ -16,14 +16,14 @@ If a query performs poorly, examine its query plan and
ask the following questio
If the plan is not choosing the optimal join order, set
`join_collapse_limit=1` and use explicit `JOIN` syntax in your SQL statement to
force the legacy query optimizer (planner) to the specified join order. You can
also collect more statistics on the relevant join columns.
- **Does the optimizer selectively scan partitioned tables?** If you use
table partitioning, is the optimizer selectively scanning only the child tables
required to satisfy the query predicates? Scans of the parent tables should
return 0 rows since the parent tables do not contain any data. See [Verifying
Your Partition Strategy](../ddl/ddl-partition.html#topic74) for an example of a
query plan that shows a selective partition scan.
-- **Does the optimizer choose hash aggregate and hash join operations
where applicable?** Hash operations are typically much faster than other types
of joins or aggregations. Row comparison and sorting is done in memory rather
than reading/writing from disk. To enable the query optimizer to choose hash
operations, there must be sufficient memory available to hold the estimated
number of rows. Try increasing work memory to improve performance for a query.
If possible, run an `EXPLAIN ANALYZE` for the query to show which plan
operations spilled to disk, how much work memory they used, and how much memory
was required to avoid spilling to disk. For example:
+- **Does the optimizer choose hash aggregate and hash join operations
where applicable?** Hash operations are typically much faster than other types
of joins or aggregations. Row comparison and sorting is done in memory rather
than reading/writing from disk. To enable the query optimizer to choose hash
operations, there must be sufficient memory available to hold the estimated
number of rows. You may wish to run an `EXPLAIN ANALYZE` for the query to
show which plan operations spilled to disk, how much work memory they used, and
how much memory was required to avoid spilling to disk. For example:
--- End diff --
Let's change "You may wish to run" to just "Run" here.
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