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From "Paul Rogers (JIRA)" <j...@apache.org>
Subject [jira] [Created] (DRILL-5198) Inefficient plan for single-slice sort query on large data
Date Mon, 16 Jan 2017 18:29:26 GMT
Paul Rogers created DRILL-5198:
----------------------------------

             Summary: Inefficient plan for single-slice sort query on large data
                 Key: DRILL-5198
                 URL: https://issues.apache.org/jira/browse/DRILL-5198
             Project: Apache Drill
          Issue Type: Bug
    Affects Versions: 1.9.0
            Reporter: Paul Rogers
            Priority: Minor


Testing of external sort revealed an unfortunate choice of plans for a somewhat pathological
query.

The query has 17 GB of data in a single CSV file. The query does nothing other than sort the
data and filter out all rows. (The purpose is to exercise the sort and discard results.) The
query was twisted to force a sort and filter (rather than the simpler Top N operator.)

Query:
{code}
select * from (select * from dfs.`/big-csv-file.csv` order by columns[0])d where d.columns[0]
= 'bogus value';
{code}

Since the goal was to test the sort, we limited execution width to a single slice on a single
node. While this is an odd case, it does represent an extreme form of resource allocation:
forcing a query to run in the minimum possible width, which may happen with admission control
on a heavily loaded cluster.

Regardless of the reason, the plan produced has two network exchanges on a single machine.
Each exchange must:

* Copy vector data to a heap buffer
* Send the data over the (loopback) network
* Release the value vectors
* Receive data into a heap buffer
* Allocate new value vectors
* Copy heap data into a value vector

The above is very costly and adds nothing to the query.

The expected plan would either:

* Run the entire query in a single minor fragment (with no exchanges), or
* Use a (not yet existing) operator to do a "mock" exchange that transfers ownership of vectors
rather than making very expensive copies.

Other issues are present as well, those will be filed as separate JIRA tickets.

The actual plan is below:

{code}
00-00    Screen : rowType = RecordType(ANY *): rowcount = 2.691360795E7, cumulative cost =
{1.6444214457450001E9 rows, 2.6992589029593388E10 cpu, 0.0 io, 3.67460460544E12 network, 2.870784848E9
memory}, id = 459
00-01      Project(*=[$0]) : rowType = RecordType(ANY *): rowcount = 2.691360795E7, cumulative
cost = {1.64173008495E9 rows, 2.698989766879839E10 cpu, 0.0 io, 3.67460460544E12 network,
2.870784848E9 memory}, id = 458
00-02        SelectionVectorRemover : rowType = RecordType(ANY T0¦¦*): rowcount = 2.691360795E7,
cumulative cost = {1.64173008495E9 rows, 2.698989766879839E10 cpu, 0.0 io, 3.67460460544E12
network, 2.870784848E9 memory}, id = 457
00-03          Filter(condition=[=(ITEM(ITEM($0, 'columns'), 0), 'ljdfhwuehnoiueyf')]) : rowType
= RecordType(ANY T0¦¦*): rowcount = 2.691360795E7, cumulative cost = {1.614816477E9 rows,
2.696298406084839E10 cpu, 0.0 io, 3.67460460544E12 network, 2.870784848E9 memory}, id = 456
00-04            Project(T0¦¦*=[$0]) : rowType = RecordType(ANY T0¦¦*): rowcount = 1.79424053E8,
cumulative cost = {1.435392424E9 rows, 2.613763341704839E10 cpu, 0.0 io, 3.67460460544E12
network, 2.870784848E9 memory}, id = 455
00-05              SingleMergeExchange(sort0=[1 ASC]) : rowType = RecordType(ANY T0¦¦*,
ANY EXPR$1): rowcount = 1.79424053E8, cumulative cost = {1.435392424E9 rows, 2.613763341704839E10
cpu, 0.0 io, 3.67460460544E12 network, 2.870784848E9 memory}, id = 454
01-01                SelectionVectorRemover : rowType = RecordType(ANY T0¦¦*, ANY EXPR$1):
rowcount = 1.79424053E8, cumulative cost = {1.255968371E9 rows, 2.470224099304839E10 cpu,
0.0 io, 2.204762763264E12 network, 2.870784848E9 memory}, id = 453
01-02                  Sort(sort0=[$1], dir0=[ASC]) : rowType = RecordType(ANY T0¦¦*, ANY
EXPR$1): rowcount = 1.79424053E8, cumulative cost = {1.076544318E9 rows, 2.452281694004839E10
cpu, 0.0 io, 2.204762763264E12 network, 2.870784848E9 memory}, id = 452
01-03                    Project(T0¦¦*=[$0], EXPR$1=[$1]) : rowType = RecordType(ANY T0¦¦*,
ANY EXPR$1): rowcount = 1.79424053E8, cumulative cost = {8.97120265E8 rows, 4.844449431E9
cpu, 0.0 io, 2.204762763264E12 network, 0.0 memory}, id = 451
01-04                      HashToRandomExchange(dist0=[[$1]]) : rowType = RecordType(ANY T0¦¦*,
ANY EXPR$1, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 1.79424053E8, cumulative cost = {8.97120265E8
rows, 4.844449431E9 cpu, 0.0 io, 2.204762763264E12 network, 0.0 memory}, id = 450
02-01                        UnorderedMuxExchange : rowType = RecordType(ANY T0¦¦*, ANY
EXPR$1, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount = 1.79424053E8, cumulative cost = {7.17696212E8
rows, 1.973664583E9 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 449
03-01                          Project(T0¦¦*=[$0], EXPR$1=[$1], E_X_P_R_H_A_S_H_F_I_E_L_D=[hash32AsDouble($1)])
: rowType = RecordType(ANY T0¦¦*, ANY EXPR$1, ANY E_X_P_R_H_A_S_H_F_I_E_L_D): rowcount =
1.79424053E8, cumulative cost = {5.38272159E8 rows, 1.79424053E9 cpu, 0.0 io, 0.0 network,
0.0 memory}, id = 448
03-02                            Project(T0¦¦*=[$0], EXPR$1=[ITEM($1, 0)]) : rowType = RecordType(ANY
T0¦¦*, ANY EXPR$1): rowcount = 1.79424053E8, cumulative cost = {3.58848106E8 rows, 1.076544318E9
cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 447
03-03                              Project(T0¦¦*=[$0], columns=[$1]) : rowType = RecordType(ANY
T0¦¦*, ANY columns): rowcount = 1.79424053E8, cumulative cost = {1.79424053E8 rows, 3.58848106E8
cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 446
03-04                                Scan(groupscan=[EasyGroupScan [selectionRoot=maprfs:/drill/testdata/resource-manager/descending-col-length-8k.tbl,
numFiles=1, columns=[`*`], files=[maprfs:///drill/testdata/resource-manager/descending-col-length-8k.tbl]]])
: rowType = (DrillRecordRow[*, columns]): rowcount = 1.79424053E8, cumulative cost = {1.79424053E8
rows, 3.58848106E8 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 445
{code}




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