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06-04-2016
04:19 PM
Drill uses Java direct memory as well as Java Heap memory to do the computation. if you have hive orc table drill will do the computation in "drill java heap memory" not in "drill direct memory" (physical memory). depending on hive storage plugin configuration (given below), During query planning phase Drill will query your metastore service driven by property 'hive.metastore.uris' to know the schema and other required information and prepare query plan. for better performance drill also support the caching of hive metadata into drill cache which is controlled by "hive.metastore.cache-ttl-seconds" and "hive.metastore.cache-expire-after".cache-ttl-seconds value can be any non-negative value, including 0, which turns caching off. The cache-expire-after value can be “access” or “write”. Access indicates expiry after a read or write operation, and write indicates expiry after a write operation only. {
"type": "hive",
"enabled": false,
"configProps": {
"hive.metastore.uris": "thrift://hostname:9083",
"hive.metastore.sasl.enabled": "false",
"fs.default.name": "hdfs://nmhostname/"
}
}
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06-04-2016
03:32 PM
4 Kudos
@Roberto Sancho metastore comes into the picture when drill tries to query data stored in hive tables and it merely used to know the schema of the hive table otherwise it has a capability to query certain datastore by evaluating schema on the fly. on most of the data store drill uses direct memory to do all the computation but for hive tables if the data it is stored in orc or parquet it leverage hive orc or hive parquet reader to query the data which eventually read the data in java heap. he keep the metastore in memory?? No,Drill do not keep compete metastore in memory, during query parsing and planning phase it query hive metastore service to know the schema so that it can validate the query and plan accordingly.
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06-03-2016
04:34 PM
3 Kudos
this is due to the memory required by orc writer while writing orc files, you can limit the memory use by tweaking the value of orc.compress.size which is of 256KB by default.I am not sure about your heap size, start testing with 8KB of buffer using alter table table_name set tblproperties("orc.compress.size"="8192") and see if it helps.
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06-03-2016
03:54 PM
4 Kudos
There is no configuration required just run the spark thrift server as a spark user using following command ./sbin/start-thriftserver.sh --master yarn-client --executor-memory 512m --hiveconf hive.server2.thrift.port=100015
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06-03-2016
01:17 PM
1 Kudo
@Kumar Sanyam
Could you please check whether antlr runtime is available in pig classpath using pig -printCmdDebug | grep antlr --color
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06-03-2016
09:47 AM
2 Kudos
you can not turn on acid on the existing table, you need to specify TBLPROPERTIES ('transactional'='true') at the time of table creation(DDL). further on this you can follow the apache documentation https://cwiki.apache.org/confluence/display/Hive/Hive+Transactions
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06-02-2016
03:48 PM
3 Kudos
with the provided logs it seems that there is some problem with nimbus or zookeeper,please check nimbus and zookeeper logs to identify the problem.
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06-02-2016
12:38 PM
1 Kudo
it looks you have not enough resources available with RM and also you are not able to check resource available due to access denied on RM UI.try to access ui by replacing http://sandbox.hortonworks.com:8042 by http://<IP_OF_SANDBOX>:8042 and ensure that your IP is reachable from your host as this is a single node so you can try yarn node -status <nm ip>
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06-02-2016
12:29 PM
good to see that worked but due to limitation with Transactional table you can not use sorted by, may be in coming future version it will be supported.
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06-02-2016
11:41 AM
1 Kudo
do you have multiple python version of python installed on your machine or your working with python testenv. what is your PYTHONPATH?
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