[jira] [Created] (HIVE-18573) Use proper Calcite operator instead of UDFs
slim bouguerra created HIVE-18573: - Summary: Use proper Calcite operator instead of UDFs Key: HIVE-18573 URL: https://issues.apache.org/jira/browse/HIVE-18573 Project: Hive Issue Type: Bug Components: Hive Reporter: slim bouguerra Currently, Hive is mostly using user-defined black box sql operators during Query planning. It will be more beneficial to use proper calcite operators. Also, Use a single name for Extract operator instead of a different name for every Unit, Same for Floor function. This will allow unifying the treatment per operator. -- This message was sent by Atlassian JIRA (v7.6.3#76005)
[jira] [Created] (HIVE-18331) Renew the Kerberos ticket used by Druid Query runner
slim bouguerra created HIVE-18331: - Summary: Renew the Kerberos ticket used by Druid Query runner Key: HIVE-18331 URL: https://issues.apache.org/jira/browse/HIVE-18331 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Druid Http Client has to renew the current user Kerberos ticket when it is close to expire. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-18254) Use proper AVG Calcite primitive instead of Other_FUNCTION
slim bouguerra created HIVE-18254:
-
Summary: Use proper AVG Calcite primitive instead of Other_FUNCTION
Key: HIVE-18254
URL: https://issues.apache.org/jira/browse/HIVE-18254
Project: Hive
Issue Type: Bug
Reporter: slim bouguerra
Currently Hive-Calcite operator tree treats AVG function as an unknown function
that has a Calcite Sql Kind of Other_FUNCTION. This is an issue that can get
into the way of rules like
{{org.apache.calcite.rel.rules.AggregateReduceFunctionsRule}}.
This patch adds the avg function to the list of known aggregate function.
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[jira] [Created] (HIVE-18226) handle UDF to double/int over aggregate
slim bouguerra created HIVE-18226:
-
Summary: handle UDF to double/int over aggregate
Key: HIVE-18226
URL: https://issues.apache.org/jira/browse/HIVE-18226
Project: Hive
Issue Type: Sub-task
Components: Druid integration
Reporter: slim bouguerra
In cases like the following query Hive planner adds extra UDFtoDouble over
integer columns.
This kind of udf can be pushed to Druid as DoubleSum instead of LongSum and
vice versa.
{code}
PREHOOK: query: EXPLAIN SELECT floor_year(`__time`), SUM(ctinyint)/ count(*)
FROM druid_table GROUP BY floor_year(`__time`)
PREHOOK: type: QUERY
POSTHOOK: query: EXPLAIN SELECT floor_year(`__time`), SUM(ctinyint)/ count(*)
FROM druid_table GROUP BY floor_year(`__time`)
POSTHOOK: type: QUERY
STAGE DEPENDENCIES:
Stage-1 is a root stage
Stage-0 depends on stages: Stage-1
STAGE PLANS:
Stage: Stage-1
Map Reduce
Map Operator Tree:
TableScan
alias: druid_table
properties:
druid.query.json
{"queryType":"timeseries","dataSource":"default.druid_table","descending":false,"granularity":"year","aggregations":[{"type":"longSum","name":"$f1","fieldName":"ctinyint"},{"type":"count","name":"$f2"}],"intervals":["1900-01-01T00:00:00.000/3000-01-01T00:00:00.000"],"context":{"skipEmptyBuckets":true}}
druid.query.type timeseries
Statistics: Num rows: 9173 Data size: 0 Basic stats: PARTIAL Column
stats: NONE
Select Operator
expressions: __time (type: timestamp with local time zone),
(UDFToDouble($f1) / UDFToDouble($f2)) (type: double)
outputColumnNames: _col0, _col1
Statistics: Num rows: 9173 Data size: 0 Basic stats: PARTIAL
Column stats: NONE
File Output Operator
compressed: false
Statistics: Num rows: 9173 Data size: 0 Basic stats: PARTIAL
Column stats: NONE
table:
input format:
org.apache.hadoop.mapred.SequenceFileInputFormat
output format:
org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
Stage: Stage-0
Fetch Operator
limit: -1
Processor Tree:
ListSink
{code}
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[jira] [Created] (HIVE-18197) Fix issue with wrong segments identifier usage.
slim bouguerra created HIVE-18197: - Summary: Fix issue with wrong segments identifier usage. Key: HIVE-18197 URL: https://issues.apache.org/jira/browse/HIVE-18197 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra We have 2 different issues, that can make checking of load status fail for druid segments. issues are due to usage of wrong segment identifier at couple of locations. # We are construction the segment identifier with UTC timezone, which can be wrong if the segments we built in a different timezone. The way to fix this is to use the segment identifier instead of re-making it at the client side. # We are using outdate segments identifiers for the INSERT INTO case. The way to fix this is to use the segment metadata produced by the metadata commit phase. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-18196) Druid Mini Cluster to run Qtests integrations tests.
slim bouguerra created HIVE-18196: - Summary: Druid Mini Cluster to run Qtests integrations tests. Key: HIVE-18196 URL: https://issues.apache.org/jira/browse/HIVE-18196 Project: Hive Issue Type: Bug Reporter: slim bouguerra Assignee: Ashutosh Chauhan The overall Goal of this is to add a new Module that can fork a druid cluster to run integration testing as part of the Mini Clusters Qtest suite. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-18156) Provide smooth migration path for CTAS when time column is not with timezone
slim bouguerra created HIVE-18156:
-
Summary: Provide smooth migration path for CTAS when time column
is not with timezone
Key: HIVE-18156
URL: https://issues.apache.org/jira/browse/HIVE-18156
Project: Hive
Issue Type: Sub-task
Components: Druid integration
Reporter: slim bouguerra
Assignee: Jesus Camacho Rodriguez
Currently, default recommend CTAS and most legacy documentation does not
specify that __time column needs to be with timezone. Thus the CTAS will fail
with
{code}
2017-11-27T17:13:10,241 ERROR [e5f708c8-df4e-41a4-b8a1-d18ac13123d2 main]
ql.Driver: FAILED: SemanticException No column with timestamp with local
time-zone type on query result; one column should be of timestamp with local
time-zone type
org.apache.hadoop.hive.ql.parse.SemanticException: No column with timestamp
with local time-zone type on query result; one column should be of timestamp
with local time-zone type
at
org.apache.hadoop.hive.ql.optimizer.SortedDynPartitionTimeGranularityOptimizer$SortedDynamicPartitionProc.getGranularitySelOp(SortedDynPartitionTimeGranularityOptimizer.java:242)
at
org.apache.hadoop.hive.ql.optimizer.SortedDynPartitionTimeGranularityOptimizer$SortedDynamicPartitionProc.process(SortedDynPartitionTimeGranularityOptimizer.java:163)
at
org.apache.hadoop.hive.ql.lib.DefaultRuleDispatcher.dispatch(DefaultRuleDispatcher.java:90)
at
org.apache.hadoop.hive.ql.lib.DefaultGraphWalker.dispatchAndReturn(DefaultGraphWalker.java:105)
at
org.apache.hadoop.hive.ql.lib.DefaultGraphWalker.dispatch(DefaultGraphWalker.java:89)
at
org.apache.hadoop.hive.ql.lib.DefaultGraphWalker.walk(DefaultGraphWalker.java:158)
at
org.apache.hadoop.hive.ql.lib.DefaultGraphWalker.startWalking(DefaultGraphWalker.java:120)
at
org.apache.hadoop.hive.ql.optimizer.SortedDynPartitionTimeGranularityOptimizer.transform(SortedDynPartitionTimeGranularityOptimizer.java:103)
at
org.apache.hadoop.hive.ql.optimizer.Optimizer.optimize(Optimizer.java:250)
at
org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.analyzeInternal(SemanticAnalyzer.java:11683)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner.analyzeInternal(CalcitePlanner.java:298)
at
org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:268)
at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:592)
at org.apache.hadoop.hive.ql.Driver.compileInternal(Driver.java:1457)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1589)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1356)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1346)
at
org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:239)
at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:187)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:409)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:342)
at
org.apache.hadoop.hive.ql.QTestUtil.executeClientInternal(QTestUtil.java:1300)
at
org.apache.hadoop.hive.ql.QTestUtil.executeClient(QTestUtil.java:1274)
at
org.apache.hadoop.hive.cli.control.CoreCliDriver.runTest(CoreCliDriver.java:173)
at
org.apache.hadoop.hive.cli.control.CliAdapter.runTest(CliAdapter.java:104)
at
org.apache.hadoop.hive.cli.TestMiniDruidCliDriver.testCliDriver(TestMiniDruidCliDriver.java:59)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at
org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:47)
at
org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at
org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:44)
at
org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at
org.apache.hadoop.hive.cli.control.CliAdapter$2$1.evaluate(CliAdapter.java:92)
at org.junit.rules.RunRules.evaluate(RunRules.java:20)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:271)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:70)
at
org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:50)
at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
at org.junit.runners.ParentRunne
[jira] [Created] (HIVE-17871) Add non nullability flag to druid time column
slim bouguerra created HIVE-17871:
-
Summary: Add non nullability flag to druid time column
Key: HIVE-17871
URL: https://issues.apache.org/jira/browse/HIVE-17871
Project: Hive
Issue Type: Improvement
Components: Druid integration
Reporter: slim bouguerra
Druid time column is non null all the time.
Adding the non nullability flag will enable extra calcite goodness like
transforming
{code} select count(`__time`) from table {code} to {code} select count(*) from
table {code}
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[jira] [Created] (HIVE-17653) Druid storage handler CTAS with boolean type columns fails.
slim bouguerra created HIVE-17653:
-
Summary: Druid storage handler CTAS with boolean type columns
fails.
Key: HIVE-17653
URL: https://issues.apache.org/jira/browse/HIVE-17653
Project: Hive
Issue Type: Bug
Components: Druid integration
Reporter: slim bouguerra
Fix For: 3.0.0
Druid storage handler CTAS fails with the exception below when a Boolean column
is included.
A simple workaround would be to add a cast to string over the boolean column,
this will lead to index the column as a druid dimension with value `true` or
`false`.
{code}
ERROR : Status: Failed
ERROR : Vertex failed, vertexName=Reducer 3,
vertexId=vertex_1506230948023_0005_9_02, diagnostics=[Task failed,
taskId=task_1506230948023_0005_9_02_03, diagnostics=[TaskAttempt 0 failed,
info=[Error: Error while running task ( failure ) :
attempt_1506230948023_0005_9_02_03_0:java.lang.RuntimeException:
java.lang.RuntimeException: org.apache.hadoop.hive.ql.metadata.HiveException:
Hive Runtime Error while processing vector batch (tag=0) (vectorizedVertexNum 2)
at
org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:218)
at
org.apache.hadoop.hive.ql.exec.tez.TezProcessor.run(TezProcessor.java:172)
at
org.apache.tez.runtime.LogicalIOProcessorRuntimeTask.run(LogicalIOProcessorRuntimeTask.java:370)
at
org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:73)
at
org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:61)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1866)
at
org.apache.tez.runtime.task.TaskRunner2Callable.callInternal(TaskRunner2Callable.java:61)
at
org.apache.tez.runtime.task.TaskRunner2Callable.callInternal(TaskRunner2Callable.java:37)
at org.apache.tez.common.CallableWithNdc.call(CallableWithNdc.java:36)
at
org.apache.hadoop.hive.llap.daemon.impl.StatsRecordingThreadPool$WrappedCallable.call(StatsRecordingThreadPool.java:110)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException:
org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error while
processing vector batch (tag=0) (vectorizedVertexNum 2)
at
org.apache.hadoop.hive.ql.exec.tez.ReduceRecordSource.pushRecordVector(ReduceRecordSource.java:406)
at
org.apache.hadoop.hive.ql.exec.tez.ReduceRecordSource.pushRecord(ReduceRecordSource.java:248)
at
org.apache.hadoop.hive.ql.exec.tez.ReduceRecordProcessor.run(ReduceRecordProcessor.java:319)
at
org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:189)
... 15 more
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Hive Runtime Error
while processing vector batch (tag=0) (vectorizedVertexNum 2)
at
org.apache.hadoop.hive.ql.exec.tez.ReduceRecordSource.processVectorGroup(ReduceRecordSource.java:492)
at
org.apache.hadoop.hive.ql.exec.tez.ReduceRecordSource.pushRecordVector(ReduceRecordSource.java:397)
... 18 more
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException:
org.apache.hadoop.hive.ql.metadata.HiveException: java.io.IOException:
Dimension bo does not have STRING type: BOOLEAN
at
org.apache.hadoop.hive.ql.exec.FileSinkOperator.createBucketFiles(FileSinkOperator.java:564)
at
org.apache.hadoop.hive.ql.exec.FileSinkOperator.process(FileSinkOperator.java:664)
at
org.apache.hadoop.hive.ql.exec.vector.VectorFileSinkOperator.process(VectorFileSinkOperator.java:101)
at
org.apache.hadoop.hive.ql.exec.Operator.baseForward(Operator.java:955)
at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:903)
at
org.apache.hadoop.hive.ql.exec.vector.VectorSelectOperator.process(VectorSelectOperator.java:145)
at
org.apache.hadoop.hive.ql.exec.tez.ReduceRecordSource.processVectorGroup(ReduceRecordSource.java:479)
... 19 more
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException:
java.io.IOException: Dimension bo does not have STRING type: BOOLEAN
at
org.apache.hadoop.hive.ql.io.HiveFileFormatUtils.getHiveRecordWriter(HiveFileFormatUtils.java:272)
at
org.apache.hadoop.hive.ql.exec.FileSinkOperator.createBucketForFileIdx(FileSinkOperator.java:609)
at
org.apache.hadoop.hive.ql.exec.FileSinkOperator.createBucketFiles(FileSinkOperator.java:55
[jira] [Created] (HIVE-17627) Use druid scan query instead of the select query.
slim bouguerra created HIVE-17627: - Summary: Use druid scan query instead of the select query. Key: HIVE-17627 URL: https://issues.apache.org/jira/browse/HIVE-17627 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra The biggest difference between select query and scan query is that, scan query doesn't retain all rows in memory before rows can be returned to client. It will cause memory pressure if too many rows required by select query. Scan query doesn't have this issue. Scan query can return all rows without issuing another pagination query, which is extremely useful when query against historical or realtime node directly. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-17623) Fix Select query Fix Double column serde and some refactoring
slim bouguerra created HIVE-17623: - Summary: Fix Select query Fix Double column serde and some refactoring Key: HIVE-17623 URL: https://issues.apache.org/jira/browse/HIVE-17623 Project: Hive Issue Type: Bug Components: Druid integration Affects Versions: 3.0.0 Reporter: slim bouguerra This PR has 2 fixes. First, fixes the limit of results returned by Select query that used to be limited to 16K rows Second fixes the type inference for the double type newly added to druid. Use Jackson polymorphism to infer types and parse results from druid nodes. Removes duplicate codes form RecordReaders. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-17582) Followup of HIVE-15708
slim bouguerra created HIVE-17582:
-
Summary: Followup of HIVE-15708
Key: HIVE-17582
URL: https://issues.apache.org/jira/browse/HIVE-17582
Project: Hive
Issue Type: Bug
Components: Druid integration
Affects Versions: 3.0.0
Reporter: slim bouguerra
Assignee: slim bouguerra
HIVE-15708 commit be59e024420ed5ca970e87a6dec402fecee21f06
introduced some unwanted bugs
it did change the following code
org.apache.hadoop.hive.druid.io.DruidQueryBasedInputFormat#169
{code}
builder.intervals(Arrays.asList(DruidTable.DEFAULT_INTERVAL));
{code}
with
{code}
final List intervals = Arrays.asList();
builder.intervals(intervals);
{code}
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[jira] [Created] (HIVE-17581) Replace some calcite dependencies with native ones
slim bouguerra created HIVE-17581: - Summary: Replace some calcite dependencies with native ones Key: HIVE-17581 URL: https://issues.apache.org/jira/browse/HIVE-17581 Project: Hive Issue Type: Sub-task Components: Druid integration Affects Versions: 3.0.0 Reporter: slim bouguerra Assignee: slim bouguerra This is a followup of HIVE-17468. This patch excludes some unwanted druid-calcite dependencies. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-17523) Insert into druid table hangs Hive server2 in an infinit loop
slim bouguerra created HIVE-17523:
-
Summary: Insert into druid table hangs Hive server2 in an infinit
loop
Key: HIVE-17523
URL: https://issues.apache.org/jira/browse/HIVE-17523
Project: Hive
Issue Type: Bug
Components: Druid integration
Reporter: slim bouguerra
Inserting data via insert into table backed by druid can lead to a Hive server
hang.
This is due to some bug in the naming of druid segments partitions.
To reproduce the issue
{code}
drop table login_hive;
create table login_hive(`timecolumn` timestamp, `userid` string, `num_l`
double);
insert into login_hive values ('2015-01-01 00:00:00', 'user1', 5);
insert into login_hive values ('2015-01-01 01:00:00', 'user2', 4);
insert into login_hive values ('2015-01-01 02:00:00', 'user3', 2);
insert into login_hive values ('2015-01-02 00:00:00', 'user1', 1);
insert into login_hive values ('2015-01-02 01:00:00', 'user2', 2);
insert into login_hive values ('2015-01-02 02:00:00', 'user3', 8);
insert into login_hive values ('2015-01-03 00:00:00', 'user1', 5);
insert into login_hive values ('2015-01-03 01:00:00', 'user2', 9);
insert into login_hive values ('2015-01-03 04:00:00', 'user3', 2);
insert into login_hive values ('2015-03-09 00:00:00', 'user3', 5);
insert into login_hive values ('2015-03-09 01:00:00', 'user1', 0);
insert into login_hive values ('2015-03-09 05:00:00', 'user2', 0);
drop table login_druid;
CREATE TABLE login_druid
STORED BY 'org.apache.hadoop.hive.druid.DruidStorageHandler'
TBLPROPERTIES ("druid.datasource" = "druid_login_test_tmp",
"druid.segment.granularity" = "DAY", "druid.query.granularity" = "HOUR")
AS
select `timecolumn` as `__time`, `userid`, `num_l` FROM login_hive;
select * FROM login_druid;
insert into login_druid values ('2015-03-09 05:00:00', 'user4', 0);
{code}
This patch unifies the logic of pushing and segments naming by using Druid data
segment pusher as much as possible.
This patch also has some minor code refactoring and test enhancements.
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[jira] [Created] (HIVE-17468) Shade and package appropriate jackson version for druid storage handler
slim bouguerra created HIVE-17468: - Summary: Shade and package appropriate jackson version for druid storage handler Key: HIVE-17468 URL: https://issues.apache.org/jira/browse/HIVE-17468 Project: Hive Issue Type: Bug Reporter: slim bouguerra Fix For: 3.0.0 Currently we are excluding all the jackson core dependencies coming from druid. This is wrong in my opinion since this will lead to the packaging of unwanted jackson library from other projects. As you can see the file hive-druid-deps.txt currently jacskon core is coming from calcite and the version is 2.6.3 which is very different from 2.4.6 used by druid. This patch exclude the unwanted jars and make sure to bring in druid jackson dependency from druid it self. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-17372) update druid dependency to druid 0.10.1
slim bouguerra created HIVE-17372: - Summary: update druid dependency to druid 0.10.1 Key: HIVE-17372 URL: https://issues.apache.org/jira/browse/HIVE-17372 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra Update to most recent druid version to be released August 23. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-17303) Missmatch between roaring bitmap library used by druid and the one coming from tez
slim bouguerra created HIVE-17303:
-
Summary: Missmatch between roaring bitmap library used by druid
and the one coming from tez
Key: HIVE-17303
URL: https://issues.apache.org/jira/browse/HIVE-17303
Project: Hive
Issue Type: Bug
Components: Druid integration
Reporter: slim bouguerra
Assignee: slim bouguerra
{code}
Caused by: java.util.concurrent.ExecutionException:
java.lang.NoSuchMethodError:
org.roaringbitmap.buffer.MutableRoaringBitmap.runOptimize()Z
at
org.apache.hive.druid.com.google.common.util.concurrent.AbstractFuture$Sync.getValue(AbstractFuture.java:299)
at
org.apache.hive.druid.com.google.common.util.concurrent.AbstractFuture$Sync.get(AbstractFuture.java:286)
at
org.apache.hive.druid.com.google.common.util.concurrent.AbstractFuture.get(AbstractFuture.java:116)
at
org.apache.hadoop.hive.druid.io.DruidRecordWriter.pushSegments(DruidRecordWriter.java:165)
... 25 more
Caused by: java.lang.NoSuchMethodError:
org.roaringbitmap.buffer.MutableRoaringBitmap.runOptimize()Z
at
org.apache.hive.druid.com.metamx.collections.bitmap.WrappedRoaringBitmap.toImmutableBitmap(WrappedRoaringBitmap.java:65)
at
org.apache.hive.druid.com.metamx.collections.bitmap.RoaringBitmapFactory.makeImmutableBitmap(RoaringBitmapFactory.java:88)
at
org.apache.hive.druid.io.druid.segment.StringDimensionMergerV9.writeIndexes(StringDimensionMergerV9.java:348)
at
org.apache.hive.druid.io.druid.segment.IndexMergerV9.makeIndexFiles(IndexMergerV9.java:218)
at
org.apache.hive.druid.io.druid.segment.IndexMerger.merge(IndexMerger.java:438)
at
org.apache.hive.druid.io.druid.segment.IndexMerger.persist(IndexMerger.java:186)
at
org.apache.hive.druid.io.druid.segment.IndexMerger.persist(IndexMerger.java:152)
at
org.apache.hive.druid.io.druid.segment.realtime.appenderator.AppenderatorImpl.persistHydrant(AppenderatorImpl.java:996)
at
org.apache.hive.druid.io.druid.segment.realtime.appenderator.AppenderatorImpl.access$200(AppenderatorImpl.java:93)
at
org.apache.hive.druid.io.druid.segment.realtime.appenderator.AppenderatorImpl$2.doCall(AppenderatorImpl.java:385)
at
org.apache.hive.druid.io.druid.common.guava.ThreadRenamingCallable.call(ThreadRenamingCallable.java:44)
... 4 more
]], Vertex did not succeed due to OWN_TASK_FAILURE, failedTasks:1
killedTasks:89, Vertex vertex_1502470020457_0005_12_05 [Reducer 2]
killed/failed due to:OWN_TASK_FAILURE]DAG did not succeed due to
VERTEX_FAILURE. failedVertices:1 killedVertices:0 (state=08S01,code=2)
Options
Attachments
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[jira] [Created] (HIVE-17302) ReduceRecordSource should not add batch string to Exception message
slim bouguerra created HIVE-17302: - Summary: ReduceRecordSource should not add batch string to Exception message Key: HIVE-17302 URL: https://issues.apache.org/jira/browse/HIVE-17302 Project: Hive Issue Type: Bug Reporter: slim bouguerra ReduceRecordSource is adding the batch data as a string to the exception stack, this can lead to an OOM of the Query AM when the query fails due to other issue. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-17160) Adding kerberos Authorization to the Druid hive integration
slim bouguerra created HIVE-17160: - Summary: Adding kerberos Authorization to the Druid hive integration Key: HIVE-17160 URL: https://issues.apache.org/jira/browse/HIVE-17160 Project: Hive Issue Type: New Feature Components: Druid integration Reporter: slim bouguerra This goal of this feature is to allow hive querying a secured druid cluster using kerberos credentials. -- This message was sent by Atlassian JIRA (v6.4.14#64029)
[jira] [Created] (HIVE-16816) Chained Group by support for druid.
slim bouguerra created HIVE-16816:
-
Summary: Chained Group by support for druid.
Key: HIVE-16816
URL: https://issues.apache.org/jira/browse/HIVE-16816
Project: Hive
Issue Type: Sub-task
Components: Druid integration
Reporter: slim bouguerra
This is more likely to be a calcite enhancement but am logging it here to track
it any way.
Currently queries like {code} select count (distinct dim) from table {code} is
pushed partially to druid as group by dim followed by a count executed by hive
QE. This can be enhanced by using the nested (eg chained execution) group by
query such as the first (inner) GB query does group by key and the second
(outer) does the count.
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[jira] [Created] (HIVE-16588) Ressource leak by druid http client
slim bouguerra created HIVE-16588: - Summary: Ressource leak by druid http client Key: HIVE-16588 URL: https://issues.apache.org/jira/browse/HIVE-16588 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Fix For: 3.0.0 Current implementation of druid storage handler does leak some resources if the creation of the http client fails due to too many files exception. The reason this is leaking is the fact the cleaning hook is registered after the client starts. In order to fix this will extract the creation of the HTTP client to become static and reusable instead of per query creation. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16522) Hive is query timer is not keeping track of the fetch task execution
slim bouguerra created HIVE-16522: - Summary: Hive is query timer is not keeping track of the fetch task execution Key: HIVE-16522 URL: https://issues.apache.org/jira/browse/HIVE-16522 Project: Hive Issue Type: Bug Reporter: slim bouguerra Assignee: slim bouguerra Currently Hive CLI query execution time does not include fetch time execution. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16519) Fix exception thrown by checkOutputSpecs
slim bouguerra created HIVE-16519: - Summary: Fix exception thrown by checkOutputSpecs Key: HIVE-16519 URL: https://issues.apache.org/jira/browse/HIVE-16519 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra do not throw exception by checkOutputSpecs -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16482) Druid Ser/Desr need to use dimension output name in order to function with Extraction function
slim bouguerra created HIVE-16482:
-
Summary: Druid Ser/Desr need to use dimension output name in order
to function with Extraction function
Key: HIVE-16482
URL: https://issues.apache.org/jira/browse/HIVE-16482
Project: Hive
Issue Type: Bug
Reporter: slim bouguerra
Druid Ser/Desr need to use dimension output name in order to function with
Extraction function.
Some part of the Ser/Desr code uses the method {code}
DimensionSpec.getDimension(){code} although when extraction function are in
game the name of the dimension will be defined by
{code}DimensionSpec.getOutputName() {code}
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[jira] [Created] (HIVE-16404) Renaming of public classes in Calcite 12 breeaking druid integration
slim bouguerra created HIVE-16404: - Summary: Renaming of public classes in Calcite 12 breeaking druid integration Key: HIVE-16404 URL: https://issues.apache.org/jira/browse/HIVE-16404 Project: Hive Issue Type: Bug Components: Druid integration Affects Versions: 2.2.0 Reporter: slim bouguerra Fix For: 3.0.0 Changes to names in the druid rules is backward incompatible with current implementation. https://github.com/apache/calcite/commit/a89c62cd6d6cc181c90881afa0bf099746739a91 -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16371) Add bitmap selection strategy for druid storage handler
slim bouguerra created HIVE-16371: - Summary: Add bitmap selection strategy for druid storage handler Key: HIVE-16371 URL: https://issues.apache.org/jira/browse/HIVE-16371 Project: Hive Issue Type: Improvement Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra Currently only Concise Bitmap strategy is supported. This Pr is to make Roaring bitmap encoding the default and Concise optional if needed. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16210) Use jvm temporary tmp dir by default
slim bouguerra created HIVE-16210: - Summary: Use jvm temporary tmp dir by default Key: HIVE-16210 URL: https://issues.apache.org/jira/browse/HIVE-16210 Project: Hive Issue Type: Improvement Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra instead of using "/tmp" by default, it makes more sense to use the jvm default tmp dir. This can have dramatic consequences if the indexed files are huge. For instance application run by run containers can be provisioned with a dedicated tmp dir. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16149) Druid query path fails when using LLAP mode
slim bouguerra created HIVE-16149:
-
Summary: Druid query path fails when using LLAP mode
Key: HIVE-16149
URL: https://issues.apache.org/jira/browse/HIVE-16149
Project: Hive
Issue Type: Sub-task
Components: Druid integration
Reporter: slim bouguerra
Assignee: Ashutosh Chauhan
{code}
hive> select i_item_desc ,i_category ,i_class ,i_current_price ,i_item_id
,sum(ss_ext_sales_price)
> as itemrevenue ,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price))
over (partition by i_class) as revenueratio
> from tpcds_store_sales_sold_time_1000_day_all
> where (i_category ='Jewelry' or i_category = 'Sports' or i_category
='Books') and `__time` >= cast('2001-01-12' as date) and `__time` <=
cast('2001-02-11' as date)
> group by i_item_id ,i_item_desc ,i_category ,i_class ,i_current_price
order by i_category ,i_class ,i_item_id ,i_item_desc ,revenueratio limit 10;
Query ID = sbouguerra_20170308131436_225330b7-1142-4e4e-a05a-46ef544c8ee8
Total jobs = 1
Launching Job 1 out of 1
Status: Running (Executing on YARN cluster with App id
application_1488231257387_1862)
--
VERTICES MODESTATUS TOTAL COMPLETED RUNNING PENDING
FAILED KILLED
--
Map 1 llapINITED 1 001
0 0
Reducer 2 llapINITED 2 002
0 0
Reducer 3 llapINITED 1 001
0 0
--
VERTICES: 00/03 [>>--] 0%ELAPSED TIME: 59.68 s
--
Status: Failed
Dag received [DAG_TERMINATE, SERVICE_PLUGIN_ERROR] in RUNNING state.
Error reported by TaskScheduler [[2:LLAP]][SERVICE_UNAVAILABLE] No LLAP Daemons
are running
Vertex killed, vertexName=Reducer 3, vertexId=vertex_1488231257387_1862_3_02,
diagnostics=[Vertex received Kill while in RUNNING state., Vertex did not
succeed due to DAG_TERMINATED, failedTasks:0 killedTasks:1, Vertex
vertex_1488231257387_1862_3_02 [Reducer 3] killed/failed due to:DAG_TERMINATED]
Vertex killed, vertexName=Reducer 2, vertexId=vertex_1488231257387_1862_3_01,
diagnostics=[Vertex received Kill while in RUNNING state., Vertex did not
succeed due to DAG_TERMINATED, failedTasks:0 killedTasks:2, Vertex
vertex_1488231257387_1862_3_01 [Reducer 2] killed/failed due to:DAG_TERMINATED]
Vertex killed, vertexName=Map 1, vertexId=vertex_1488231257387_1862_3_00,
diagnostics=[Vertex received Kill while in RUNNING state., Vertex did not
succeed due to DAG_TERMINATED, failedTasks:0 killedTasks:1, Vertex
vertex_1488231257387_1862_3_00 [Map 1] killed/failed due to:DAG_TERMINATED]
DAG did not succeed due to SERVICE_PLUGIN_ERROR. failedVertices:0
killedVertices:3
FAILED: Execution Error, return code 2 from
org.apache.hadoop.hive.ql.exec.tez.TezTask. Dag received [DAG_TERMINATE,
SERVICE_PLUGIN_ERROR] in RUNNING state.Error reported by TaskScheduler
[[2:LLAP]][SERVICE_UNAVAILABLE] No LLAP Daemons are runningVertex killed,
vertexName=Reducer 3, vertexId=vertex_1488231257387_1862_3_02,
diagnostics=[Vertex received Kill while in RUNNING state., Vertex did not
succeed due to DAG_TERMINATED, failedTasks:0 killedTasks:1, Vertex
vertex_1488231257387_1862_3_02 [Reducer 3] killed/failed due
to:DAG_TERMINATED]Vertex killed, vertexName=Reducer 2,
vertexId=vertex_1488231257387_1862_3_01, diagnostics=[Vertex received Kill
while in RUNNING state., Vertex did not succeed due to DAG_TERMINATED,
failedTasks:0 killedTasks:2, Vertex vertex_1488231257387_1862_3_01 [Reducer 2]
killed/failed due to:DAG_TERMINATED]Vertex killed, vertexName=Map 1,
vertexId=vertex_1488231257387_1862_3_00, diagnostics=[Vertex received Kill
while in RUNNING state., Vertex did not succeed due to DAG_TERMINATED,
failedTasks:0 killedTasks:1, Vertex vertex_1488231257387_1862_3_00 [Map 1]
killed/failed due to:DAG_TERMINATED]DAG did not succeed due to
SERVICE_PLUGIN_ERROR. failedVertices:0 killedVertices:3
{code}
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[jira] [Created] (HIVE-16126) push all the time extraction to druid
slim bouguerra created HIVE-16126: - Summary: push all the time extraction to druid Key: HIVE-16126 URL: https://issues.apache.org/jira/browse/HIVE-16126 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra currently we don't push most of the time extractions to druid which leads to selecting all the data, bad!. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16125) Split work between reducers.
slim bouguerra created HIVE-16125: - Summary: Split work between reducers. Key: HIVE-16125 URL: https://issues.apache.org/jira/browse/HIVE-16125 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Split work between reducer. currently we have one reducer per segment granularity even if the interval will be partitioned over multiple partitions. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16124) Drop the segments data as soon it is pushed to HDFS
slim bouguerra created HIVE-16124: - Summary: Drop the segments data as soon it is pushed to HDFS Key: HIVE-16124 URL: https://issues.apache.org/jira/browse/HIVE-16124 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Drop the pushed segments from the indexer as soon as the HDFS push is done. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16123) Let user chose the granularity of bucketing.
slim bouguerra created HIVE-16123: - Summary: Let user chose the granularity of bucketing. Key: HIVE-16123 URL: https://issues.apache.org/jira/browse/HIVE-16123 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Currently we index the data with granularity of none which puts lot of pressure on the indexer. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16122) NPE Hive Druid split introduced by HIVE-15928
slim bouguerra created HIVE-16122: - Summary: NPE Hive Druid split introduced by HIVE-15928 Key: HIVE-16122 URL: https://issues.apache.org/jira/browse/HIVE-16122 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-16096) Predicate `__time` In ("date", "date") is not pused
slim bouguerra created HIVE-16096:
-
Summary: Predicate `__time` In ("date", "date") is not pused
Key: HIVE-16096
URL: https://issues.apache.org/jira/browse/HIVE-16096
Project: Hive
Issue Type: Bug
Reporter: slim bouguerra
{code}
explain select * from login_druid where `__time` in ("2003-1-1", "2004-1-1" );
OK
Plan optimized by CBO.
Stage-0
Fetch Operator
limit:-1
Select Operator [SEL_2]
Output:["_col0","_col1","_col2"]
Filter Operator [FIL_4]
predicate:(__time) IN ('2003-1-1', '2004-1-1')
TableScan [TS_0]
Output:["__time","userid","num_l"],properties:{"druid.query.json":"{\"queryType\":\"select\",\"dataSource\":\"druid_user_login\",\"descending\":false,\"intervals\":[\"1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z\"],\"dimensions\":[\"userid\"],\"metrics\":[\"num_l\"],\"granularity\":\"all\",\"pagingSpec\":{\"threshold\":16384},\"context\":{\"druid.query.fetch\":false}}","druid.query.type":"select"}
{code}
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[jira] [Created] (HIVE-16095) Filter generation is not taking into account the column type.
slim bouguerra created HIVE-16095:
-
Summary: Filter generation is not taking into account the column
type.
Key: HIVE-16095
URL: https://issues.apache.org/jira/browse/HIVE-16095
Project: Hive
Issue Type: Bug
Reporter: slim bouguerra
We are suppose to get alphanumeric comparison when we have a cast to numeric
type. This looks like to be a calcite issue.
{code}
hive> explain select * from login_druid where userid < 2
> ;
OK
Plan optimized by CBO.
Stage-0
Fetch Operator
limit:-1
Select Operator [SEL_1]
Output:["_col0","_col1","_col2"]
TableScan [TS_0]
Output:["__time","userid","num_l"],properties:{"druid.query.json":"{\"queryType\":\"select\",\"dataSource\":\"druid_user_login\",\"descending\":false,\"intervals\":[\"1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z\"],\"filter\":{\"type\":\"bound\",\"dimension\":\"userid\",\"upper\":\"2\",\"upperStrict\":true,\"alphaNumeric\":false},\"dimensions\":[\"userid\"],\"metrics\":[\"num_l\"],\"granularity\":\"all\",\"pagingSpec\":{\"threshold\":16384},\"context\":{\"druid.query.fetch\":false}}","druid.query.type":"select"}
Time taken: 1.548 seconds, Fetched: 10 row(s)
hive> explain select * from login_druid where cast (userid as int) < 2;
OK
Plan optimized by CBO.
Stage-0
Fetch Operator
limit:-1
Select Operator [SEL_1]
Output:["_col0","_col1","_col2"]
TableScan [TS_0]
Output:["__time","userid","num_l"],properties:{"druid.query.json":"{\"queryType\":\"select\",\"dataSource\":\"druid_user_login\",\"descending\":false,\"intervals\":[\"1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z\"],\"filter\":{\"type\":\"bound\",\"dimension\":\"userid\",\"upper\":\"2\",\"upperStrict\":true,\"alphaNumeric\":false},\"dimensions\":[\"userid\"],\"metrics\":[\"num_l\"],\"granularity\":\"all\",\"pagingSpec\":{\"threshold\":16384},\"context\":{\"druid.query.fetch\":false}}","druid.query.type":"select"}
Time taken: 0.27 seconds, Fetched: 10 row(s)
{code}
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[jira] [Created] (HIVE-16026) Generated query will timeout and/or kill the druid cluster.
slim bouguerra created HIVE-16026:
-
Summary: Generated query will timeout and/or kill the druid
cluster.
Key: HIVE-16026
URL: https://issues.apache.org/jira/browse/HIVE-16026
Project: Hive
Issue Type: Bug
Components: Druid integration
Reporter: slim bouguerra
Grouping by `__time` and another dimension generate a query with granularity
NONE with an interval from 1970 to 3000. This will kill the druid cluster
because druid group by strategy will create cursor for every ms and there is
lot of milliseconds between 1970 and 3000. Hence such query can turn into a
select then do the group by within hive. This should only happen when we don't
know the `__time` granularity.
{code}
explain select `__time`, userid from login_druid group by `__time`, userid
> ;
OK
Plan optimized by CBO.
Stage-0
Fetch Operator
limit:-1
Select Operator [SEL_1]
Output:["_col0","_col1"]
TableScan [TS_0]
Output:["__time","userid"],properties:{"druid.query.json":"{\"queryType\":\"groupBy\",\"dataSource\":\"druid_user_login\",\"granularity\":\"NONE\",\"dimensions\":[\"userid\"],\"limitSpec\":{\"type\":\"default\"},\"aggregations\":[{\"type\":\"longSum\",\"name\":\"dummy_agg\",\"fieldName\":\"dummy_agg\"}],\"intervals\":[\"1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z\"]}","druid.query.type":"groupBy"}
{code}
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[jira] [Created] (HIVE-16025) Where IN clause throws exception
slim bouguerra created HIVE-16025:
-
Summary: Where IN clause throws exception
Key: HIVE-16025
URL: https://issues.apache.org/jira/browse/HIVE-16025
Project: Hive
Issue Type: Bug
Components: Druid integration
Reporter: slim bouguerra
Priority: Critical
{code}
select * from login_druid where userid IN ("user1", "user2");
Exception in thread "main" java.lang.AssertionError: cannot translate filter:
IN($1, _UTF-16LE'user1', _UTF-16LE'user2')
at
org.apache.calcite.adapter.druid.DruidQuery$Translator.translateFilter(DruidQuery.java:886)
at
org.apache.calcite.adapter.druid.DruidQuery$Translator.access$000(DruidQuery.java:786)
at
org.apache.calcite.adapter.druid.DruidQuery.getQuery(DruidQuery.java:424)
at
org.apache.calcite.adapter.druid.DruidQuery.deriveQuerySpec(DruidQuery.java:402)
at
org.apache.calcite.adapter.druid.DruidQuery.getQuerySpec(DruidQuery.java:351)
at
org.apache.calcite.adapter.druid.DruidQuery.deriveRowType(DruidQuery.java:271)
at
org.apache.calcite.rel.AbstractRelNode.getRowType(AbstractRelNode.java:219)
at
org.apache.calcite.plan.RelOptUtil.verifyTypeEquivalence(RelOptUtil.java:343)
at
org.apache.calcite.plan.hep.HepRuleCall.transformTo(HepRuleCall.java:57)
at
org.apache.calcite.plan.RelOptRuleCall.transformTo(RelOptRuleCall.java:225)
at
org.apache.calcite.adapter.druid.DruidRules$DruidFilterRule.onMatch(DruidRules.java:142)
at
org.apache.calcite.plan.AbstractRelOptPlanner.fireRule(AbstractRelOptPlanner.java:314)
at org.apache.calcite.plan.hep.HepPlanner.applyRule(HepPlanner.java:502)
at
org.apache.calcite.plan.hep.HepPlanner.applyRules(HepPlanner.java:381)
at
org.apache.calcite.plan.hep.HepPlanner.executeInstruction(HepPlanner.java:247)
at
org.apache.calcite.plan.hep.HepInstruction$RuleInstance.execute(HepInstruction.java:125)
at
org.apache.calcite.plan.hep.HepPlanner.executeProgram(HepPlanner.java:206)
at
org.apache.calcite.plan.hep.HepPlanner.findBestExp(HepPlanner.java:193)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner$CalcitePlannerAction.hepPlan(CalcitePlanner.java:1775)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner$CalcitePlannerAction.apply(CalcitePlanner.java:1504)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner$CalcitePlannerAction.apply(CalcitePlanner.java:1260)
at org.apache.calcite.tools.Frameworks$1.apply(Frameworks.java:113)
at
org.apache.calcite.prepare.CalcitePrepareImpl.perform(CalcitePrepareImpl.java:997)
at org.apache.calcite.tools.Frameworks.withPrepare(Frameworks.java:149)
at org.apache.calcite.tools.Frameworks.withPlanner(Frameworks.java:106)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner.logicalPlan(CalcitePlanner.java:1068)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner.getOptimizedAST(CalcitePlanner.java:1084)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner.genOPTree(CalcitePlanner.java:363)
at
org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.analyzeInternal(SemanticAnalyzer.java:11026)
at
org.apache.hadoop.hive.ql.parse.CalcitePlanner.analyzeInternal(CalcitePlanner.java:285)
at
org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:258)
at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:511)
at org.apache.hadoop.hive.ql.Driver.compileInternal(Driver.java:1317)
at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1457)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1237)
at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1227)
at
org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:233)
at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:184)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:403)
at
org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:821)
at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:759)
at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:686)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:233)
at org.apache.hadoop.util.RunJar.main(RunJar.java:148)
{code}
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[jira] [Created] (HIVE-15951) Make sure base persist directory is unique and deleted
slim bouguerra created HIVE-15951: - Summary: Make sure base persist directory is unique and deleted Key: HIVE-15951 URL: https://issues.apache.org/jira/browse/HIVE-15951 Project: Hive Issue Type: Bug Components: Druid integration Affects Versions: 2.2.0 Reporter: slim bouguerra Priority: Critical Fix For: 2.2.0 In some cases the base persist directory will contain old data or shared between reducer in the same physical VM. That will lead to the failure of the job till that the directory is cleaned. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-15877) Upload dependency jars for druid storage handler
slim bouguerra created HIVE-15877: - Summary: Upload dependency jars for druid storage handler Key: HIVE-15877 URL: https://issues.apache.org/jira/browse/HIVE-15877 Project: Hive Issue Type: Bug Reporter: slim bouguerra Upload dependency jars for druid storage handler -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-15809) Typo in the PostgreSQL database name for druid service
slim bouguerra created HIVE-15809: - Summary: Typo in the PostgreSQL database name for druid service Key: HIVE-15809 URL: https://issues.apache.org/jira/browse/HIVE-15809 Project: Hive Issue Type: Bug Components: Druid integration Affects Versions: 2.2.0 Reporter: slim bouguerra Assignee: slim bouguerra Priority: Trivial Fix For: 2.2.0 -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-15785) Add S3 support for druid storage handler
slim bouguerra created HIVE-15785: - Summary: Add S3 support for druid storage handler Key: HIVE-15785 URL: https://issues.apache.org/jira/browse/HIVE-15785 Project: Hive Issue Type: Sub-task Components: Druid integration Reporter: slim bouguerra Fix For: 2.2.0 Add S3 support for druid storage handler -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Created] (HIVE-15727) Add pre insert work to give storage handler the possibility to perform pre insert checking
slim bouguerra created HIVE-15727: - Summary: Add pre insert work to give storage handler the possibility to perform pre insert checking Key: HIVE-15727 URL: https://issues.apache.org/jira/browse/HIVE-15727 Project: Hive Issue Type: Sub-task Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra Fix For: 2.2.0 Add pre insert work stage to give storage handler the possibility to perform pre insert checking. For instance for the druid storage handler this will block the statement INSERT INTO statement. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (HIVE-15586) Make Insert and Create statement Transactional
slim bouguerra created HIVE-15586: - Summary: Make Insert and Create statement Transactional Key: HIVE-15586 URL: https://issues.apache.org/jira/browse/HIVE-15586 Project: Hive Issue Type: Sub-task Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra Currently insert/create will return the handle to user without waiting for the data been loaded by the druid cluster. In order to avoid that will add a passive wait till the segment are loaded by historical in case the coordinator is UP. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (HIVE-15571) Support Insert into for druid storage handler
slim bouguerra created HIVE-15571: - Summary: Support Insert into for druid storage handler Key: HIVE-15571 URL: https://issues.apache.org/jira/browse/HIVE-15571 Project: Hive Issue Type: New Feature Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (HIVE-15439) Support INSERT OVERWRITE for internal druid datasources.
slim bouguerra created HIVE-15439: - Summary: Support INSERT OVERWRITE for internal druid datasources. Key: HIVE-15439 URL: https://issues.apache.org/jira/browse/HIVE-15439 Project: Hive Issue Type: Sub-task Components: Druid integration Affects Versions: 2.2.0 Reporter: slim bouguerra Assignee: slim bouguerra Add support for SQL statement INSERT OVERWRITE TABLE druid_internal_table. In order to add this support will need to add new post insert hook to update the druid metadata. Creation of the segment will be the same as CTAS. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (HIVE-15393) Update Guava version
slim bouguerra created HIVE-15393: - Summary: Update Guava version Key: HIVE-15393 URL: https://issues.apache.org/jira/browse/HIVE-15393 Project: Hive Issue Type: Sub-task Components: Druid integration Affects Versions: 2.2.0 Reporter: slim bouguerra Priority: Blocker Druid base code is using newer version of guava 16.0.1 that is not compatible with the current version used by Hive. FYI Hadoop project is moving to Guava 18 not sure if it is better to move to guava 18 or even 19. https://issues.apache.org/jira/browse/HADOOP-10101 -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (HIVE-15277) Teach Hive how to create/delete Druid segments
slim bouguerra created HIVE-15277:
-
Summary: Teach Hive how to create/delete Druid segments
Key: HIVE-15277
URL: https://issues.apache.org/jira/browse/HIVE-15277
Project: Hive
Issue Type: Bug
Components: Druid integration
Affects Versions: 2.2.0
Reporter: slim bouguerra
Assignee: slim bouguerra
We want to extend the DruidStorageHandler to support CTAS queries.
In this implementation Hive will generate druid segment files and insert the
metadata to signal the handoff to druid.
The syntax will be as follows:
CREATE TABLE druid_table_1
STORED BY 'org.apache.hadoop.hive.druid.DruidStorageHandler'
TBLPROPERTIES ("druid.datasource" = "datasourcename")
AS ;
This statement stores the results of query in a Druid datasource
named 'datasourcename'. One of the columns of the query needs to be the time
dimension, which is mandatory in Druid. In particular, we use the same
convention that it is used for Druid: there needs to be a the column named
'__time' in the result of the executed query, which will act as the time
dimension column in Druid. Currently, the time column dimension needs to be a
'timestamp' type column.
metrics can be of type long, double and float while dimensions are strings.
Keep in mind that druid has a clear separation between dimensions and metrics,
therefore if you have a column in hive that contains number and need to be
presented as dimension use the cast operator to cast as string.
This initial implementation interacts with Druid Meta data storage to
add/remove the table in druid, user need to supply the meta data config as
--hiveconf hive.druid.metadata.password=XXX --hiveconf
hive.druid.metadata.username=druid --hiveconf
hive.druid.metadata.uri=jdbc:mysql://host/druid
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[jira] [Created] (HIVE-15274) wrong results on the column __time
slim bouguerra created HIVE-15274: - Summary: wrong results on the column __time Key: HIVE-15274 URL: https://issues.apache.org/jira/browse/HIVE-15274 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Assignee: Jesus Camacho Rodriguez Priority: Minor issuing select * from table will return wrong time column. expected results ─┬┬─┐ │ __time │ dimension1 │ metric1 │ ├─┼┼─┤ │ Wed Dec 31 2014 16:00:00 GMT-0800 (PST) │ value1 │ 1 │ │ Wed Dec 31 2014 16:00:00 GMT-0800 (PST) │ value1.1 │ 1 │ │ Sun May 31 2015 19:00:00 GMT-0700 (PDT) │ value2 │ 20.5│ │ Sun May 31 2015 19:00:00 GMT-0700 (PDT) │ value2.1 │ 32 │ └─┴┴─┘ returned result 2014-12-31 19:00:00 value1 1.0 2014-12-31 19:00:00 value1.11.0 2014-12-31 19:00:00 value2 20.5 2014-12-31 19:00:00 value2.132.0 -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (HIVE-15273) Http Client not configured correctly
slim bouguerra created HIVE-15273: - Summary: Http Client not configured correctly Key: HIVE-15273 URL: https://issues.apache.org/jira/browse/HIVE-15273 Project: Hive Issue Type: Bug Components: Druid integration Reporter: slim bouguerra Assignee: slim bouguerra Priority: Minor Current used http client by the druid-hive record reader is constructed with default values. Default values of numConnection and ReadTimeout are very small which can lead to following exception " ERROR [2ee34a2b-c8a5-4748-ab91-db3621d2aa5c main] CliDriver: Failed with exception java.io.IOException:java.io.IOException: java.io.IOException: org.apache.h ive.druid.org.jboss.netty.channel.ChannelException: Channel disconnected" Full stack can be found here.https://gist.github.com/b-slim/384ca6a96698f5b51ad9b171cff556a2 -- This message was sent by Atlassian JIRA (v6.3.4#6332)
