[jira] [Created] (HIVE-26082) Upgrade DataNucleus dependency to 5.2.6

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-26082:


 Summary: Upgrade DataNucleus dependency to 5.2.6
 Key: HIVE-26082
 URL: https://issues.apache.org/jira/browse/HIVE-26082
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Upgrade 5.2.4 to 5.2.6



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[jira] [Created] (HIVE-26081) Upgrade ant to 1.10.9

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-26081:


 Summary: Upgrade ant to 1.10.9
 Key: HIVE-26081
 URL: https://issues.apache.org/jira/browse/HIVE-26081
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Upgrade org.apache.ant:ant from 1.9.1 to 1.10.9 to fix the vulnerability 
CVE-2020-11979



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[jira] [Created] (HIVE-26080) Upgrade accumulo-core to 1.10.1

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-26080:


 Summary: Upgrade accumulo-core to 1.10.1
 Key: HIVE-26080
 URL: https://issues.apache.org/jira/browse/HIVE-26080
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Upgrade org.apache.accumulo:accumulo-core from 1.7.0 to 1.10.1 to fix the 
vulnerability CVE-2020-17533



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[jira] [Created] (HIVE-26079) Upgrade protobuf to 3.16.1

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-26079:


 Summary: Upgrade protobuf to 3.16.1
 Key: HIVE-26079
 URL: https://issues.apache.org/jira/browse/HIVE-26079
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Upgrade com.google.protobuf:protobuf-java from 2.5.0 to 3.16.1 to fix 
CVE-2021-22569



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[jira] [Created] (HIVE-26078) Upgrade gson to 2.8.9

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-26078:


 Summary: Upgrade gson to 2.8.9
 Key: HIVE-26078
 URL: https://issues.apache.org/jira/browse/HIVE-26078
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Upgrade to version com.google.code.gson:gson:2.8.9 to avoid WS-2021-0419



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[jira] [Created] (HIVE-25693) Vector implementation return Incorrect results for STDDEV, STDDEV_SAMP, STDDEV_POP for floating point data types.

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25693:


 Summary: Vector implementation return Incorrect results for 
STDDEV, STDDEV_SAMP, STDDEV_POP for floating point data types.
 Key: HIVE-25693
 URL: https://issues.apache.org/jira/browse/HIVE-25693
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma






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[jira] [Created] (HIVE-25678) java.lang.ClassCastException in COALESCE()

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25678:


 Summary: java.lang.ClassCastException in COALESCE()
 Key: HIVE-25678
 URL: https://issues.apache.org/jira/browse/HIVE-25678
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Caused by: java.lang.ClassCastException: org.apache.hadoop.io.IntWritable 
cannot be cast to org.apache.hadoop.io.BooleanWritable
at 
org.apache.hadoop.hive.serde2.objectinspector.primitive.WritableBooleanObjectInspector.get(WritableBooleanObjectInspector.java:36)
at 
org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorUtils.getBoolean(PrimitiveObjectInspectorUtils.java:514)
at 
org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorConverter$BooleanConverter.convert(PrimitiveObjectInspectorConverter.java:67)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils$ReturnObjectInspectorResolver.convertIfNecessary(GenericUDFUtils.java:247)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils$ReturnObjectInspectorResolver.convertIfNecessary(GenericUDFUtils.java:213)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFWhen.evaluate(GenericUDFWhen.java:105)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:197)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqual.evaluate(GenericUDFOPEqual.java:114)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:197)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFWhen.evaluate(GenericUDFWhen.java:96)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:197)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFWhen.evaluate(GenericUDFWhen.java:96)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:197)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPAnd.evaluate(GenericUDFOPAnd.java:65)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:197)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator$DeferredExprObject.get(ExprNodeGenericFuncEvaluator.java:88)
at 
org.apache.hadoop.hive.ql.udf.generic.GenericUDFWhen.evaluate(GenericUDFWhen.java:93)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:197)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluatorHead._evaluate(ExprNodeEvaluatorHead.java:44)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:80)
at 
org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:68)
at 
org.apache.hadoop.hive.ql.exec.SelectOperator.process(SelectOperator.java:88)



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[jira] [Created] (HIVE-25653) Precision problem in STD, STDDDEV_SAMP,STDDEV_POP

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25653:


 Summary: Precision problem in STD, STDDDEV_SAMP,STDDEV_POP
 Key: HIVE-25653
 URL: https://issues.apache.org/jira/browse/HIVE-25653
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description





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[jira] [Created] (HIVE-25577) unix_timestamp() is ignoring the time zone value

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25577:


 Summary: unix_timestamp() is ignoring the time zone value
 Key: HIVE-25577
 URL: https://issues.apache.org/jira/browse/HIVE-25577
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


set hive.local.time.zone=Asia/Bangkok;

Query - SELECT FROM_UNIXTIME(UNIX_TIMESTAMP('2000-01-07 00:00:00 
GMT','-MM-dd HH:mm:ss z'));

Result - 2000-01-07 00:00:00 ICT



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[jira] [Created] (HIVE-25576) Raise exception instead of silent change for new DateFormatter

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25576:


 Summary: Raise exception instead of silent change for new 
DateFormatter
 Key: HIVE-25576
 URL: https://issues.apache.org/jira/browse/HIVE-25576
 Project: Hive
  Issue Type: Improvement
Affects Versions: 4.0.0
Reporter: Ashish Sharma
Assignee: Ashish Sharma


*Hive 1.2* - 

VM time zone set to Asia/Bangkok

Query - SELECT FROM_UNIXTIME(UNIX_TIMESTAMP('1800-01-01 00:00:00 
UTC','-MM-dd HH:mm:ss z'));

Result - 1800-01-01 07:00:00

*Master branch* - 

set hive.local.time.zone=Asia/Bangkok;

Query - SELECT FROM_UNIXTIME(UNIX_TIMESTAMP('1800-01-01 00:00:00 
UTC','-MM-dd HH:mm:ss z'));

Result - 1800-01-01 06:42:04






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[jira] [Created] (HIVE-25535) Adding table property "NO_CLEANUP"

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25535:


 Summary: Adding table property "NO_CLEANUP"
 Key: HIVE-25535
 URL: https://issues.apache.org/jira/browse/HIVE-25535
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Add "NO_CLEANUP" in the table properties enable/disable the table-level cleanup 
and prevent the cleaner process from automatically cleaning obsolete 
directories/files.

Example - 

ALTER TABLE  SET TBLPROPERTIES('NO_CLEANUP'=FALSE/TRUE);



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[jira] [Created] (HIVE-25458) combination of from_unixtime and unix_timestamp is giving wrong result

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25458:


 Summary: combination of from_unixtime and unix_timestamp is giving 
wrong result
 Key: HIVE-25458
 URL: https://issues.apache.org/jira/browse/HIVE-25458
 Project: Hive
  Issue Type: Bug
Reporter: Ashish Sharma


Description - 

set hive.local.time.zone=Asia/Bangkok;

select from_unixtime(unix_timestamp('1400-11-08 01:53:11'));
Result - 1400-11-17 01:35:15
Expected - 1400-11-08 01:53:11

select from_unixtime(unix_timestamp('1800-11-08 01:53:11'));
Result - 1800-11-08 01:35:15
Expected - 1800-11-08 01:53:11

select from_unixtime(unix_timestamp('1400-11-08 08:00:00 ICT', '-MM-dd 
HH:mm:ss z'));
Result 1400-11-17 07:42:04
Expected 1400-11-08 08:00:00 


select from_unixtime(unix_timestamp('1800-11-08 08:00:00 ICT', '-MM-dd 
HH:mm:ss z'));
Result - 1800-11-08 07:42:04
Expected - 1800-11-08 08:00:00 









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[jira] [Created] (HIVE-25392) Refactor UDFToInteger to GenericUDFToInteger

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25392:


 Summary: Refactor UDFToInteger to GenericUDFToInteger
 Key: HIVE-25392
 URL: https://issues.apache.org/jira/browse/HIVE-25392
 Project: Hive
  Issue Type: Sub-task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Refactor UDFToInteger to move from UDF to GenericUDF.




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[jira] [Created] (HIVE-25351) stddev(), sstddev_pop() with CBO enable returning null

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25351:


 Summary: stddev(), sstddev_pop() with CBO enable returning null
 Key: HIVE-25351
 URL: https://issues.apache.org/jira/browse/HIVE-25351
 Project: Hive
  Issue Type: Bug
Reporter: Ashish Sharma
Assignee: Ashish Sharma


script used to repro

create table cbo_test (key string, v1 double, v2 decimal(30,2), v3 
decimal(30,2));

insert into cbo_test values ("00140006375905", 10230.72, 
10230.72, 10230.69), ("00140006375905", 10230.72, 10230.72, 
10230.69), ("00140006375905", 10230.72, 10230.72, 10230.69), 
("00140006375905", 10230.72, 10230.72, 10230.69), 
("00140006375905", 10230.72, 10230.72, 10230.69), 
("00140006375905", 10230.72, 10230.72, 10230.69);

select stddev(v1), stddev(v2), stddev(v3) from cbo_test;


Enable CBO
++
|  Explain   |
++
| Plan optimized by CBO. |
||
| Vertex dependency in root stage|
| Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE)|
||
| Stage-0|
|   Fetch Operator   |
| limit:-1   |
| Stage-1|
|   Reducer 2 vectorized |
|   File Output Operator [FS_13] |
| Select Operator [SEL_12] (rows=1 width=24) |
|   Output:["_col0","_col1","_col2"] |
|   Group By Operator [GBY_11] (rows=1 width=72) |
| 
Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","count(VALUE._col2)","sum(VALUE._col3)","sum(VALUE._col4)","count(VALUE._col5)","sum(VALUE._col6)","sum(VALUE._col7)","count(VALUE._col8)"]
 |
|   <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized  |
| PARTITION_ONLY_SHUFFLE [RS_10] |
|   Group By Operator [GBY_9] (rows=1 width=72) |
| 
Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"],aggregations:["sum(_col3)","sum(_col0)","count(_col0)","sum(_col5)","sum(_col4)","count(_col1)","sum(_col7)","sum(_col6)","count(_col2)"]
 |
| Select Operator [SEL_8] (rows=6 width=232) |
|   
Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] |
|   TableScan [TS_0] (rows=6 width=232) |
| default@cbo_test,cbo_test, ACID 
table,Tbl:COMPLETE,Col:COMPLETE,Output:["v1","v2","v3"] |
||
++



Disable CBO
++
|  Explain   |
++
| Vertex dependency in root stage|
| Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE)|
||
| Stage-0|
|   Fetch Operator   |
| limit:-1   |
| Stage-1|
|   Reducer 2 vectorized |
|   File Output Operator [FS_11] |
| Group By Operator [GBY_10] (rows=1 width=24) |
|   
Output:["_col0","_col1","_col2"],aggregations:["stddev(VALUE._col0)","stddev(VALUE._col1)","stddev(VALUE._col2)"]
 |
| <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized|
|   PARTITION_ONLY_SHUFFLE [RS_9]|
| Group By Operator [GBY_8] (rows=1 width=240) |
|   
Output:["_col0","_col1","_col2"],aggregations:["stddev(v1)","stddev(v2)","stddev(v3)"]
 |
|   Select Operator [SEL_7] (rows=6 width=232) |
| Output:["v1","v2","v3"]|
| TableScan [TS_0] (rows=6 width=232) |
|   default@cbo_test,cbo_test, ACID 
table,Tbl:COMPLETE,Col:COMPLETE,Output:["v1","v2","v3"] |
||
++




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[jira] [Created] (HIVE-25340) Refactor UDFToByte to GenericUDFToByte

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25340:


 Summary: Refactor UDFToByte to GenericUDFToByte
 Key: HIVE-25340
 URL: https://issues.apache.org/jira/browse/HIVE-25340
 Project: Hive
  Issue Type: Sub-task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

Move implementation of UDFToByte from old UDF.class to GenericUDFToByte with 
GenericUDF.class


 



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[jira] [Created] (HIVE-25339) Refactor UDFToBoolean to GenericUDFToBoolean

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25339:


 Summary: Refactor UDFToBoolean to GenericUDFToBoolean
 Key: HIVE-25339
 URL: https://issues.apache.org/jira/browse/HIVE-25339
 Project: Hive
  Issue Type: Sub-task
  Components: UDF
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description - 

1. Move UDFToBoolean.class from old UDF.Class implementation to new 
GenericUDF.class
2. Refactor redundant code.



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[jira] [Created] (HIVE-25334) Refactor UDF CAST( as TIMESTAMP)

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25334:


 Summary: Refactor UDF CAST( as TIMESTAMP)
 Key: HIVE-25334
 URL: https://issues.apache.org/jira/browse/HIVE-25334
 Project: Hive
  Issue Type: Sub-task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description 

Refactor GenericUDFTimestamp.class 


DOD
Refactor 



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[jira] [Created] (HIVE-25333) Refactor Existing UDF

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25333:


 Summary: Refactor Existing UDF
 Key: HIVE-25333
 URL: https://issues.apache.org/jira/browse/HIVE-25333
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma


Description

Most of the UDF code is write in 2013 no changes has done after since in UDF. 

Objective of this EPIC - 
1. Refactor all existing UDF implementation from UDF.class to GenericUDF.class
2. Clean the up the code to reduce code duplication


DOD
Refactor all UDF



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[jira] [Created] (HIVE-25332) refactor UDF CAST( as DATE)

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25332:


 Summary: refactor UDF CAST( as DATE)
 Key: HIVE-25332
 URL: https://issues.apache.org/jira/browse/HIVE-25332
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

CAST( as DATE) is done by GenericUDFToDate.class which is written 
back in 2013 and hasn't been refactor after since also there is code duplicate 
as well.


DOD
Refactor entire UDF 



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[jira] [Created] (HIVE-25306) Move Date and Timestamp parsing from ResolverStyle.LENIENT to ResolverStyle.STRICT

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25306:


 Summary: Move Date and Timestamp parsing from 
ResolverStyle.LENIENT to ResolverStyle.STRICT
 Key: HIVE-25306
 URL: https://issues.apache.org/jira/browse/HIVE-25306
 Project: Hive
  Issue Type: Bug
  Components: Query Planning, UDF
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description - 

Currently Date.java and Timestamp.java use DateTimeFormatter for parsing to 
convert the date/timpstamp from int,string,char etc to Date or Timestamp. 

Default DateTimeFormatter which use ResolverStyle.LENIENT which mean date like 
"1992-13-12" is converted to "2000-01-12", 

Moving DateTimeFormatter which use ResolverStyle.STRICT which mean date like 
"1992-13-12" is not be converted instead null is return.



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[jira] [Created] (HIVE-25297) Refactor GenericUDFDateDiff

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25297:


 Summary: Refactor GenericUDFDateDiff
 Key: HIVE-25297
 URL: https://issues.apache.org/jira/browse/HIVE-25297
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

Remove redundant code and refactor entire GenericUDFDateDiff



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[jira] [Created] (HIVE-25233) Removing deprecated unix_timestamp() UDF

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25233:


 Summary: Removing deprecated unix_timestamp() UDF
 Key: HIVE-25233
 URL: https://issues.apache.org/jira/browse/HIVE-25233
 Project: Hive
  Issue Type: Task
  Components: UDF
Affects Versions: All Versions
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

Since unix_timestamp() UDF was deprecated as part of 
https://issues.apache.org/jira/browse/HIVE-10728. Internal 
GenericUDFUnixTimeStamp extend GenericUDFToUnixTimeStamp and call 
to_utc_timestamp() for unix_timestamp(string date) & unix_timestamp(string 
date, string pattern).


unix_timestamp()   => CURRENT_TIMESTAMP
unix_timestamp(string date) => to_utc_timestamp()
unix_timestamp(string date, string pattern) => to_utc_timestamp()


We should clean up unix_timestamp() and points to to_utc_timestamp()
   




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[jira] [Created] (HIVE-25098) [CVE-2020-13949] Upgrade thrift from 0.13.0 to 0.14.0 due

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25098:


 Summary: [CVE-2020-13949] Upgrade thrift from 0.13.0 to 0.14.0 due
 Key: HIVE-25098
 URL: https://issues.apache.org/jira/browse/HIVE-25098
 Project: Hive
  Issue Type: Bug
Affects Versions: All Versions
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Upgrading thrift from 0.13.0 to 0.14.0 due to 

https://nvd.nist.gov/vuln/detail/CVE-2020-13949




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[jira] [Created] (HIVE-25093) date_format() UDF is returning values in UTC time zone only

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25093:


 Summary: date_format() UDF is returning values in UTC time zone 
only 
 Key: HIVE-25093
 URL: https://issues.apache.org/jira/browse/HIVE-25093
 Project: Hive
  Issue Type: Bug
  Components: UDF
Affects Versions: 3.1.2
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Query - select date_format(current_timestamp,"-MM-dd HH:mm:ss.SSS z")

Result - 2021-05-04 13:00:33.358 UTC

https://issues.apache.org/jira/browse/HIVE-12192 
As part of above jira it was decided to have a common time zone for all 
computation i.e. "UTC". Due to which data_format() function was hard coded to 
"UTC".

https://issues.apache.org/jira/browse/HIVE-21039
But later it was decided that user session time zone value should be the 
default not UTC. 

date_format() was not fixed as part of HIVE-21039.

Dropping this mail to understand what should be the ideal time zone value of 
date_format().



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[jira] [Created] (HIVE-25078) [cachedstore]

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-25078:


 Summary: [cachedstore]
 Key: HIVE-25078
 URL: https://issues.apache.org/jira/browse/HIVE-25078
 Project: Hive
  Issue Type: Sub-task
  Components: Standalone Metastore
Affects Versions: 4.0.0
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

Add Table id check in following while extracting (i.e. get call) cached table 
from cached store
1. Table
2. Partitions
3. Constrains 



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[jira] [Created] (HIVE-24344) [cache store] Add valid flag in table wrapper for all constraint

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24344:


 Summary: [cache store] Add valid flag in table wrapper for all 
constraint 
 Key: HIVE-24344
 URL: https://issues.apache.org/jira/browse/HIVE-24344
 Project: Hive
  Issue Type: Task
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

Currently if get null for a constraint value we fall back to raw store to 
validate weather NULL is correct or not. We can add a valid flag which states 
that NULL constraint value is correct and thus reduce raw store call.

DOD
Add flag for all 6 constraint in cachedstore



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[jira] [Created] (HIVE-24261) Create Drop_all_table_constraint api in standalone hive metastore

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24261:


 Summary: Create Drop_all_table_constraint api in standalone hive 
metastore  
 Key: HIVE-24261
 URL: https://issues.apache.org/jira/browse/HIVE-24261
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Currently in order to drop all constraint multiple call are need to instead can 
we have a single api which will drop all constraint of the given table.



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[jira] [Created] (HIVE-24260) create api create_table_with_constraints with SQLAllTableConstraint

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24260:


 Summary: create api create_table_with_constraints with 
SQLAllTableConstraint
 Key: HIVE-24260
 URL: https://issues.apache.org/jira/browse/HIVE-24260
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Create api create api create_table_with_constraints with 
SQLAllTableConstraint.class in standalone hivemetastore



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[jira] [Created] (HIVE-24259) [CachedStore] Optimise getAlltableConstraint from 6 cache call to 1 cache call

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24259:


 Summary: [CachedStore] Optimise getAlltableConstraint from 6 cache 
call to 1 cache call
 Key: HIVE-24259
 URL: https://issues.apache.org/jira/browse/HIVE-24259
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description -
currently inorder to get all constraint form the cachedstore. 6 different call 
is made to the store. Instead combine that 6 call in 1



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[jira] [Created] (HIVE-24258) Make standalone metastore cachedStore case-insenstive

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24258:


 Summary: Make standalone metastore cachedStore case-insenstive
 Key: HIVE-24258
 URL: https://issues.apache.org/jira/browse/HIVE-24258
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description

Objects like table name, db name, column name etc are case incentives as per 
HIVE contract but standalone metastore cachedstore is case sensitive.  



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[jira] [Created] (HIVE-24257) Wrong check constraint naming in Hive metastore

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24257:


 Summary: Wrong check constraint naming in Hive metastore
 Key: HIVE-24257
 URL: https://issues.apache.org/jira/browse/HIVE-24257
 Project: Hive
  Issue Type: Bug
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Current 

struct SQLCheckConstraint {
  1: string catName, // catalog name
  2: string table_db,// table schema
  3: string table_name,  // table name
  4: string column_name, // column name
  5: string check_expression,// check expression
  6: string dc_name, // default name
  7: bool enable_cstr,   // Enable/Disable
  8: bool validate_cstr, // Validate/No validate
  9: bool rely_cstr  // Rely/No Rely
}


Naming for CheckConstraint is wrong it should be cc_name instead of dc_name




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[jira] [Created] (HIVE-24214) Reduce alter_table() function overloading in metastore

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24214:


 Summary: Reduce alter_table() function overloading in metastore
 Key: HIVE-24214
 URL: https://issues.apache.org/jira/browse/HIVE-24214
 Project: Hive
  Issue Type: Improvement
  Components: Standalone Metastore
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Reduce following overloading method to less number of methods

void alter_table(String catName, String dbName, String tblName, Table newTable,
  EnvironmentContext envContext)
  throws InvalidOperationException, MetaException, TException;

default void alter_table(String catName, String dbName, String tblName, Table 
newTable)
  throws InvalidOperationException, MetaException, TException {
alter_table(catName, dbName, tblName, newTable, null);
  }  

@Deprecated
  void alter_table(String defaultDatabaseName, String tblName, Table table,
  boolean cascade) throws InvalidOperationException, MetaException, 
TException;

@Deprecated
  void alter_table_with_environmentContext(String databaseName, String tblName, 
Table table,
  EnvironmentContext environmentContext) throws InvalidOperationException, 
MetaException,
  TException;

  void alter_table(String catName, String databaseName, String tblName, Table 
table,
  EnvironmentContext environmentContext, String validWriteIdList)
  throws InvalidOperationException, MetaException, TException;






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[jira] [Created] (HIVE-24091) Replace multiple constraints call with getAllTableConstraints api call in query planner

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24091:


 Summary: Replace multiple constraints call with 
getAllTableConstraints api call in query planner
 Key: HIVE-24091
 URL: https://issues.apache.org/jira/browse/HIVE-24091
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Inorder get all the constraints of table i.e. PrimaryKey, ForeignKey, 
UniqueConstraint ,NotNullConstraint ,DefaultConstraint ,CheckConstraint. We 
have to do 6 different metastore call. Replace these call with one  
getAllTableConstraints  api which provide all the constraints at once



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[jira] [Created] (HIVE-24062) Combine all table constrains RDBMS calls in one SQL call

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24062:


 Summary: Combine all table constrains RDBMS calls in one SQL call
 Key: HIVE-24062
 URL: https://issues.apache.org/jira/browse/HIVE-24062
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Table consist of 6 different type of constrains namely 
PrimaryKey,ForeignKey,UniqueConstraint,NotNullConstraint,DefaultConstraint,CheckConstraint.
 All constrains has different SQL query to fetch the infromation from RDBMS. 
Which lead to 6 different RDBS call. 

Idea here is to have one complex query which fetch all the constrains 
information at once then filter the result set on the basis of constrains type.



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[jira] [Created] (HIVE-24056) Column stats gather stage as part of import table command plan generation

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-24056:


 Summary: Column stats gather stage as part of import table command 
plan generation 
 Key: HIVE-24056
 URL: https://issues.apache.org/jira/browse/HIVE-24056
 Project: Hive
  Issue Type: Improvement
  Components: Import/Export, Statistics
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Description - 

As of today in import table command does't have column stats gather phase as a 
part of execution plan. As a result of which no matter what 
hive.stats.autogather set to true or false. columns stats are reset while 
importing the table/partitions for all types of tables.

DOD
Adding  column stats gather stage to import plan



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[jira] [Created] (HIVE-23887) numRow property of table stats is not get exported with export command

[Ashish Sharma (Jira)]

Ashish Sharma created HIVE-23887:


 Summary: numRow property of table stats is not get exported with 
export command
 Key: HIVE-23887
 URL: https://issues.apache.org/jira/browse/HIVE-23887
 Project: Hive
  Issue Type: Bug
  Components: Import/Export, Statistics
Reporter: Ashish Sharma
Assignee: Ashish Sharma


While doing "export table db.table to '/import/table' " entire column stat is 
getting exported except numRows property 



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[jira] [Created] (HIVE-19103) Reading only required column in nested structure schema in ORC

[Ashish Sharma (JIRA)]

Ashish Sharma created HIVE-19103:


 Summary: Reading only required column in nested structure schema 
in ORC
 Key: HIVE-19103
 URL: https://issues.apache.org/jira/browse/HIVE-19103
 Project: Hive
  Issue Type: Improvement
Reporter: Ashish Sharma
Assignee: Ashish Sharma


Reading required columns only in nested structure schema

Example - 

*Current state* - 

Schema  -  struct>
Query - select c.e.f from t where c.e.f > 10;
Current state - read entire c struct from the file and then filter because 
"hive.io.file.readcolumn.ids" is referred due to which all the children column 
are select to read from the file.
Conf -
 _hive.io.file.readcolumn.ids  = "2"
 hive.io.file.readNestedColumn.paths = "c.e.f"_

Result -   
boolean[ ] include  = [true,false,false,true,true,true,true,true]

*Expected state* -

Schema  -  struct>
Query - select c.e.f from t where c.e.f > 10;
Expected state - instead of reading entire c struct from the file just read 
only the f column by referring the  " hive.io.file.readNestedColumn.paths".
Conf -
 _hive.io.file.readcolumn.ids  = "2"
 hive.io.file.readNestedColumn.paths = "c.e.f"_

Result -   
boolean[ ] include  = [true,false,false,true,false,true,true,false]




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