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Posted to issues@hive.apache.org by "Harsh Maheshwari (Jira)" <ji...@apache.org> on 2020/01/22 11:12:00 UTC
[jira] [Updated] (HIVE-22759) Default decimal round off producing
incorrect results in "Vectorized" mode
[ https://issues.apache.org/jira/browse/HIVE-22759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Harsh Maheshwari updated HIVE-22759:
------------------------------------
Description:
Premise:
External table on top of a parquet file. The table contains decimal with a fixed scale, and there could be entries in parquet with higher scale. Hive, by default rounds off the values to the scale defined in table schema and uses a view of translated values while applying filters.
Steps to reproduce -
a. Create a new HDFS path and [upload attached parquet files|https://drive.google.com/file/d/1sUg-ovWku9X4AmmwQND2hzg5yIKVTy9q/view?usp=sharing] within the folder.
b. Create an external table managing these parquet files
{noformat}
create table lineitem_15_3(l_orderkey int, l_suppkey int, l_linenumber int, l_quantity decimal(15,3), l_extendedprice decimal(15,3), l_discount decimal(15,3), l_tax decimal(15,3), l_returnflag string, l_linestatus string, l_shipdate date, l_commitdate date, l_receiptdate date, l_shipinstruct string, l_shipmode string, l_comment string) stored as parquet location 'hdfs://<location>';
{noformat}
c. Execute following query in vectorized and non-vectorized mode -
{noformat}
select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax>= 0.001 and l_orderkey = 107695104;
{noformat}
----
Non vectorized mode produces correct result (1 row) -
{noformat}
hive> set hive.vectorized.execution.enabled = false;
hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax >= 0.001 and l_orderkey = 107695104; Query ID = hive_20200122101124_3734cfab-6cbb-4562-97ee-71e15775babe Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1579669891475_0048, Tracking URL = <...> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0048 Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0 2020-01-22 10:11:30,661 Stage-1 map = 0%, reduce = 0% 2020-01-22 10:11:39,833 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 7.45 sec 2020-01-22 10:11:46,961 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 25.22 sec MapReduce Total cumulative CPU time: 25 seconds 220 msec Ended Job = job_1579669891475_0048 MapReduce Jobs Launched: Stage-Stage-1: Map: 2 Cumulative CPU: 25.22 sec HDFS Read: 318375885 HDFS Write: 310 SUCCESS Total MapReduce CPU Time Spent: 25 seconds 220 msec
OK
107695104 263020 6 1.000 918.026 0.006 0.001 N O 1995-06-21 1995-08-08 1995-07-14 TAKE BACK RETURN FOB thely express reques
Time taken: 23.24 seconds, Fetched: 1 row(s)
{noformat}
----
Vectorized mode produces incorrect result (no rows) -
{noformat}
hive> set hive.vectorized.execution.enabled = true;
hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax >= 0.001 and l_orderkey = 107695104;
Query ID = hive_20200122101058_3cda8d56-0885-4c31-aff4-6686a84f639e
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1579669891475_0047, Tracking URL = <...>
Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0047
Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0
2020-01-22 10:11:04,474 Stage-1 map = 0%, reduce = 0%
2020-01-22 10:11:12,651 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 5.29 sec
2020-01-22 10:11:16,735 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 20.6 sec
MapReduce Total cumulative CPU time: 20 seconds 600 msec
Ended Job = job_1579669891475_0047
MapReduce Jobs Launched:
Stage-Stage-1: Map: 2 Cumulative CPU: 20.6 sec HDFS Read: 318378365 HDFS Write: 174 SUCCESS
Total MapReduce CPU Time Spent: 20 seconds 600 msec
OK
Time taken: 19.822 seconds{noformat}
Similar behaviour is observed for many other queries. The record in parquet file has a value of 0.00075 for l_tax. Since, schema defines 3 digits of scale in decimal points, it should match with 0.001 after rounding off and return the row.
If we explicitly apply round() function to scale of 3 on l_tax column, the row shows up correctly.
{noformat}
hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and round(l_tax,3) >= 0.001 and l_orderkey = 107695104; Query ID = hive_20200122103950_c5d579b8-770f-441d-bfaa-74c84ac3c515 Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1579669891475_0049, Tracking URL = <...> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0049 Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0 2020-01-22 10:39:56,751 Stage-1 map = 0%, reduce = 0% 2020-01-22 10:40:03,894 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 8.63 sec 2020-01-22 10:40:12,044 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 27.01 sec MapReduce Total cumulative CPU time: 27 seconds 10 msec Ended Job = job_1579669891475_0049 MapReduce Jobs Launched: Stage-Stage-1: Map: 2 Cumulative CPU: 27.01 sec HDFS Read: 318376023 HDFS Write: 310 SUCCESS Total MapReduce CPU Time Spent: 27 seconds 10 msec
OK
107695104 263020 6 1.000 918.026 0.006 0.001 N O 1995-06-21 1995-08-08 1995-07-14 TAKE BACK RETURN FOB thely express reques
Time taken: 22.888 seconds, Fetched: 1 row(s)
{noformat}
----
This proves, there's an issue with default round up, in vectorisation mode.
was:
Premise:
External table on top of a parquet file. The table contains decimal with a fixed scale, and there could be entries in parquet with higher scale. Hive, by default rounds off the values to the scale defined in table schema and uses a view of translated values while applying filters.
Steps to reproduce -
a. Create a new HDFS path and upload attached parquet files within the folder.
b. Create an external table managing these parquet files
{noformat}
create table lineitem_15_3(l_orderkey int, l_suppkey int, l_linenumber int, l_quantity decimal(15,3), l_extendedprice decimal(15,3), l_discount decimal(15,3), l_tax decimal(15,3), l_returnflag string, l_linestatus string, l_shipdate date, l_commitdate date, l_receiptdate date, l_shipinstruct string, l_shipmode string, l_comment string) stored as parquet location 'hdfs://<location>';
{noformat}
c. Execute following query in vectorized and non-vectorized mode -
{noformat}
select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax>= 0.001 and l_orderkey = 107695104;
{noformat}
----
Non vectorized mode produces correct result (1 row) -
{noformat}
hive> set hive.vectorized.execution.enabled = false;
hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax >= 0.001 and l_orderkey = 107695104; Query ID = hive_20200122101124_3734cfab-6cbb-4562-97ee-71e15775babe Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1579669891475_0048, Tracking URL = <...> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0048 Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0 2020-01-22 10:11:30,661 Stage-1 map = 0%, reduce = 0% 2020-01-22 10:11:39,833 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 7.45 sec 2020-01-22 10:11:46,961 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 25.22 sec MapReduce Total cumulative CPU time: 25 seconds 220 msec Ended Job = job_1579669891475_0048 MapReduce Jobs Launched: Stage-Stage-1: Map: 2 Cumulative CPU: 25.22 sec HDFS Read: 318375885 HDFS Write: 310 SUCCESS Total MapReduce CPU Time Spent: 25 seconds 220 msec
OK
107695104 263020 6 1.000 918.026 0.006 0.001 N O 1995-06-21 1995-08-08 1995-07-14 TAKE BACK RETURN FOB thely express reques
Time taken: 23.24 seconds, Fetched: 1 row(s)
{noformat}
----
Vectorized mode produces incorrect result (no rows) -
{noformat}
hive> set hive.vectorized.execution.enabled = true;
hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax >= 0.001 and l_orderkey = 107695104;
Query ID = hive_20200122101058_3cda8d56-0885-4c31-aff4-6686a84f639e
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1579669891475_0047, Tracking URL = <...>
Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0047
Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0
2020-01-22 10:11:04,474 Stage-1 map = 0%, reduce = 0%
2020-01-22 10:11:12,651 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 5.29 sec
2020-01-22 10:11:16,735 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 20.6 sec
MapReduce Total cumulative CPU time: 20 seconds 600 msec
Ended Job = job_1579669891475_0047
MapReduce Jobs Launched:
Stage-Stage-1: Map: 2 Cumulative CPU: 20.6 sec HDFS Read: 318378365 HDFS Write: 174 SUCCESS
Total MapReduce CPU Time Spent: 20 seconds 600 msec
OK
Time taken: 19.822 seconds{noformat}
Similar behaviour is observed for many other queries. The record in parquet file has a value of 0.00075 for l_tax. Since, schema defines 3 digits of scale in decimal points, it should match with 0.001 after rounding off and return the row.
If we explicitly apply round() function to scale of 3 on l_tax column, the row shows up correctly.
{noformat}
hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and round(l_tax,3) >= 0.001 and l_orderkey = 107695104; Query ID = hive_20200122103950_c5d579b8-770f-441d-bfaa-74c84ac3c515 Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1579669891475_0049, Tracking URL = <...> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0049 Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0 2020-01-22 10:39:56,751 Stage-1 map = 0%, reduce = 0% 2020-01-22 10:40:03,894 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 8.63 sec 2020-01-22 10:40:12,044 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 27.01 sec MapReduce Total cumulative CPU time: 27 seconds 10 msec Ended Job = job_1579669891475_0049 MapReduce Jobs Launched: Stage-Stage-1: Map: 2 Cumulative CPU: 27.01 sec HDFS Read: 318376023 HDFS Write: 310 SUCCESS Total MapReduce CPU Time Spent: 27 seconds 10 msec
OK
107695104 263020 6 1.000 918.026 0.006 0.001 N O 1995-06-21 1995-08-08 1995-07-14 TAKE BACK RETURN FOB thely express reques
Time taken: 22.888 seconds, Fetched: 1 row(s)
{noformat}
----
This proves, there's an issue with default round up, in vectorisation mode.
> Default decimal round off producing incorrect results in "Vectorized" mode
> --------------------------------------------------------------------------
>
> Key: HIVE-22759
> URL: https://issues.apache.org/jira/browse/HIVE-22759
> Project: Hive
> Issue Type: Bug
> Components: Vectorization
> Affects Versions: 3.1.1
> Environment: Hive on top of hadoop, operating on top of parquet files. Issue reproducible with both MR and Tez execution.
> Reporter: Harsh Maheshwari
> Priority: Major
>
> Premise:
> External table on top of a parquet file. The table contains decimal with a fixed scale, and there could be entries in parquet with higher scale. Hive, by default rounds off the values to the scale defined in table schema and uses a view of translated values while applying filters.
> Steps to reproduce -
> a. Create a new HDFS path and [upload attached parquet files|https://drive.google.com/file/d/1sUg-ovWku9X4AmmwQND2hzg5yIKVTy9q/view?usp=sharing] within the folder.
> b. Create an external table managing these parquet files
> {noformat}
> create table lineitem_15_3(l_orderkey int, l_suppkey int, l_linenumber int, l_quantity decimal(15,3), l_extendedprice decimal(15,3), l_discount decimal(15,3), l_tax decimal(15,3), l_returnflag string, l_linestatus string, l_shipdate date, l_commitdate date, l_receiptdate date, l_shipinstruct string, l_shipmode string, l_comment string) stored as parquet location 'hdfs://<location>';
> {noformat}
> c. Execute following query in vectorized and non-vectorized mode -
> {noformat}
> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax>= 0.001 and l_orderkey = 107695104;
> {noformat}
>
> ----
> Non vectorized mode produces correct result (1 row) -
> {noformat}
> hive> set hive.vectorized.execution.enabled = false;
> hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax >= 0.001 and l_orderkey = 107695104; Query ID = hive_20200122101124_3734cfab-6cbb-4562-97ee-71e15775babe Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1579669891475_0048, Tracking URL = <...> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0048 Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0 2020-01-22 10:11:30,661 Stage-1 map = 0%, reduce = 0% 2020-01-22 10:11:39,833 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 7.45 sec 2020-01-22 10:11:46,961 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 25.22 sec MapReduce Total cumulative CPU time: 25 seconds 220 msec Ended Job = job_1579669891475_0048 MapReduce Jobs Launched: Stage-Stage-1: Map: 2 Cumulative CPU: 25.22 sec HDFS Read: 318375885 HDFS Write: 310 SUCCESS Total MapReduce CPU Time Spent: 25 seconds 220 msec
> OK
> 107695104 263020 6 1.000 918.026 0.006 0.001 N O 1995-06-21 1995-08-08 1995-07-14 TAKE BACK RETURN FOB thely express reques
> Time taken: 23.24 seconds, Fetched: 1 row(s)
> {noformat}
>
> ----
> Vectorized mode produces incorrect result (no rows) -
> {noformat}
> hive> set hive.vectorized.execution.enabled = true;
>
> hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and l_tax >= 0.001 and l_orderkey = 107695104;
> Query ID = hive_20200122101058_3cda8d56-0885-4c31-aff4-6686a84f639e
> Total jobs = 1
> Launching Job 1 out of 1
> Number of reduce tasks is set to 0 since there's no reduce operator
> Starting Job = job_1579669891475_0047, Tracking URL = <...>
> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0047
> Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0
> 2020-01-22 10:11:04,474 Stage-1 map = 0%, reduce = 0%
> 2020-01-22 10:11:12,651 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 5.29 sec
> 2020-01-22 10:11:16,735 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 20.6 sec
> MapReduce Total cumulative CPU time: 20 seconds 600 msec
> Ended Job = job_1579669891475_0047
> MapReduce Jobs Launched:
> Stage-Stage-1: Map: 2 Cumulative CPU: 20.6 sec HDFS Read: 318378365 HDFS Write: 174 SUCCESS
> Total MapReduce CPU Time Spent: 20 seconds 600 msec
> OK
> Time taken: 19.822 seconds{noformat}
>
> Similar behaviour is observed for many other queries. The record in parquet file has a value of 0.00075 for l_tax. Since, schema defines 3 digits of scale in decimal points, it should match with 0.001 after rounding off and return the row.
> If we explicitly apply round() function to scale of 3 on l_tax column, the row shows up correctly.
> {noformat}
> hive> select * from lineitem_15_3 where l_extendedprice <= 918.031 and l_discount >= 0.0 and round(l_tax,3) >= 0.001 and l_orderkey = 107695104; Query ID = hive_20200122103950_c5d579b8-770f-441d-bfaa-74c84ac3c515 Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1579669891475_0049, Tracking URL = <...> Kill Command = /opt/hadoop/bin/mapred job -kill job_1579669891475_0049 Hadoop job information for Stage-1: number of mappers: 2; number of reducers: 0 2020-01-22 10:39:56,751 Stage-1 map = 0%, reduce = 0% 2020-01-22 10:40:03,894 Stage-1 map = 50%, reduce = 0%, Cumulative CPU 8.63 sec 2020-01-22 10:40:12,044 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 27.01 sec MapReduce Total cumulative CPU time: 27 seconds 10 msec Ended Job = job_1579669891475_0049 MapReduce Jobs Launched: Stage-Stage-1: Map: 2 Cumulative CPU: 27.01 sec HDFS Read: 318376023 HDFS Write: 310 SUCCESS Total MapReduce CPU Time Spent: 27 seconds 10 msec
> OK
> 107695104 263020 6 1.000 918.026 0.006 0.001 N O 1995-06-21 1995-08-08 1995-07-14 TAKE BACK RETURN FOB thely express reques
> Time taken: 22.888 seconds, Fetched: 1 row(s)
> {noformat}
> ----
>
> This proves, there's an issue with default round up, in vectorisation mode.
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