Thanks Gopal.

I added a compact index to this table as below on 5 columns

hive> show formatted indexes on sales2;
OK
idx_name                tab_name                col_names
idx_tab_name            idx_type                comment

sales2_idx              sales2                  prod_id, cust_id, time_id,
channel_id, promo_id oraclehadoop__sales2_sales2_idx__       compact

But as I expected it,  CBO ignores it

STAGE PLANS:
  Stage: Stage-0
    Fetch Operator
      limit: -1
      Processor Tree:
        TableScan
          alias: sales2
          Statistics: Num rows: 22052232 Data size: 6527460672 Basic stats:
COMPLETE Column stats: NONE
          Filter Operator
            predicate: (((((prod_id = 13) and (cust_id = 50833)) and
(UDFToString(time_id) = '2000-12-26 00:00:00')) and (channel_id = 2)) and
(promo_id = 999)) (type: boolean)
            Statistics: Num rows: 689132 Data size: 203983072 Basic stats:
COMPLETE Column stats: NONE
            Select Operator
              expressions: 13 (type: bigint), 50833 (type: bigint),
2000-12-26 00:00:00.0 (type: timestamp), 2 (type: bigint), 999 (type:
bigint), quantity_sold (type: decimal(10,0)), amount_sold (type:
decimal(10,0))
              outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5,
_col6
              Statistics: Num rows: 689132 Data size: 203983072 Basic
stats: COMPLETE Column stats: NONE
              ListSink

thanks


Dr Mich Talebzadeh



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On 27 June 2016 at 17:38, Gopal Vijayaraghavan <gop...@apache.org> wrote:

> > It appears to me that Spark does not rely on statistics that are
> >collected by Hive on say ORC tables.
> > It seems that Spark uses its own optimization to query the Hive tables
> >irrespective of Hive has collected by way of statistics etc?
>
> Spark does not have a cost based optimizer yet - please follow this JIRA,
> which suggests that it is planned for the future.
>
> <https://issues.apache.org/jira/browse/SPARK-16026>
>
>
> > CLUSTERED BY (PROD_ID,CUST_ID,TIME_ID,CHANNEL_ID,PROMO_ID) INTO 256
> >BUCKETS
> ...
> > Table is sorted in the order of prod_id, cust_id,time_id, channel_id and
> >promo_id. It has 22 million rows.
>
> Not it is not.
>
> Due to whatever backwards compatbilitiy brain-damage of Hive-1, CLUSTERED
> BY *DOES* not CLUSTER at all.
>
> Add at least
>
> SORTED BY (PROD_ID)
>
> if what you care about is scanning performance with the ORC indexes.
>
>
> > And Hive on Spark returns the same 24 rows in 30 seconds
>
> That sounds slow for 22 million rows. That should be a 5-6 second query in
> Hive on a single 16-core box.
>
> Is this a build from source? Has the build got log4j1.x with INFO/DEBUG?
>
> > Assuming that the time taken will be optimization time + query time then
> >it appears that in most cases the optimization time does not really make
> >that impact on the overall performance?
>
> The optimizer's impact is most felt when you have 3+ joins - computing
> join order, filter transitivity etc.
>
> In this case, all the optimizer does is simplify predicates.
>
> Cheers,
> Gopal
>
>
>

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