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From ayan guha <guha.a...@gmail.com>
Subject Re: Pyspark Error: Unable to read a hive table with transactional property set as 'True'
Date Fri, 02 Mar 2018 21:45:09 GMT
Hi

Couple of questions:

1. It seems the error is due to number format:
Caused by: java.util.concurrent.ExecutionException:
java.lang.NumberFormatException:
For input string: "0003024_0000"
        at java.util.concurrent.FutureTask.report(FutureTask.java:122)
        at java.util.concurrent.FutureTask.get(FutureTask.java:192)
        at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.
generateSplitsInfo(OrcInputFormat.java:998)
        ... 75 more
Why do you think it is due to ACID?

2. You should not be creating Hive Context again in REPL, no need for that.
REPL already reports: SparkContext available as sc, HiveContext available
as sqlContext.

3. Have you tried the same with spark 2.x?



On Sat, Mar 3, 2018 at 5:00 AM, Debabrata Ghosh <mailfordebu@gmail.com>
wrote:

> Hi All,
>                        Greetings ! I needed some help to read a Hive table
> via Pyspark for which the transactional property is set to 'True' (In other
> words ACID property is enabled). Following is the entire stacktrace and the
> description of the hive table. Would you please be able to help me resolve
> the error:
>
> 18/03/01 11:06:22 INFO BlockManagerMaster: Registered BlockManager
> 18/03/01 11:06:22 INFO EventLoggingListener: Logging events to
> hdfs:///spark-history/local-1519923982155
> Welcome to
>       ____              __
>      / __/__  ___ _____/ /__
>     _\ \/ _ \/ _ `/ __/  '_/
>    /__ / .__/\_,_/_/ /_/\_\   version 1.6.3
>       /_/
>
> Using Python version 2.7.12 (default, Jul  2 2016 17:42:40)
> SparkContext available as sc, HiveContext available as sqlContext.
> >>> from pyspark.sql import HiveContext
> >>> hive_context = HiveContext(sc)
> >>> hive_context.sql("select count(*) from load_etl.trpt_geo_defect_prod_
> dec07_del_blank").show()
> 18/03/01 11:09:45 INFO HiveContext: Initializing execution hive, version
> 1.2.1
> 18/03/01 11:09:45 INFO ClientWrapper: Inspected Hadoop version:
> 2.7.3.2.6.0.3-8
> 18/03/01 11:09:45 INFO ClientWrapper: Loaded org.apache.hadoop.hive.shims.Hadoop23Shims
> for Hadoop version 2.7.3.2.6.0.3-8
> 18/03/01 11:09:46 INFO HiveMetaStore: 0: Opening raw store with
> implemenation class:org.apache.hadoop.hive.metastore.ObjectStore
> 18/03/01 11:09:46 INFO ObjectStore: ObjectStore, initialize called
> 18/03/01 11:09:46 INFO Persistence: Property hive.metastore.integral.jdo.pushdown
> unknown - will be ignored
> 18/03/01 11:09:46 INFO Persistence: Property datanucleus.cache.level2
> unknown - will be ignored
> 18/03/01 11:09:50 INFO ObjectStore: Setting MetaStore object pin classes
> with hive.metastore.cache.pinobjtypes="Table,StorageDescriptor,SerDeInfo,
> Partition,Database,Type,FieldSchema,Order"
> 18/03/01 11:09:50 INFO Datastore: The class "org.apache.hadoop.hive.metastore.model.MFieldSchema"
> is tagged as "embedded-only" so does not have its own datastore table.
> 18/03/01 11:09:50 INFO Datastore: The class "org.apache.hadoop.hive.metastore.model.MOrder"
> is tagged as "embedded-only" so does not have its own datastore table.
> 18/03/01 11:09:53 INFO Datastore: The class "org.apache.hadoop.hive.metastore.model.MFieldSchema"
> is tagged as "embedded-only" so does not have its own datastore table.
> 18/03/01 11:09:53 INFO Datastore: The class "org.apache.hadoop.hive.metastore.model.MOrder"
> is tagged as "embedded-only" so does not have its own datastore table.
> 18/03/01 11:09:54 INFO MetaStoreDirectSql: Using direct SQL, underlying DB
> is DERBY
> 18/03/01 11:09:54 INFO ObjectStore: Initialized ObjectStore
> 18/03/01 11:09:54 WARN ObjectStore: Version information not found in
> metastore. hive.metastore.schema.verification is not enabled so recording
> the schema version 1.2.0
> 18/03/01 11:09:54 WARN ObjectStore: Failed to get database default,
> returning NoSuchObjectException
> 18/03/01 11:09:54 INFO HiveMetaStore: Added admin role in metastore
> 18/03/01 11:09:54 INFO HiveMetaStore: Added public role in metastore
> 18/03/01 11:09:55 INFO HiveMetaStore: No user is added in admin role,
> since config is empty
> 18/03/01 11:09:55 INFO HiveMetaStore: 0: get_all_databases
> 18/03/01 11:09:55 INFO audit: ugi=devuser@IP.COM   ip=unknown-ip-addr
>   cmd=get_all_databases
> 18/03/01 11:09:55 INFO HiveMetaStore: 0: get_functions: db=default pat=*
> 18/03/01 11:09:55 INFO audit: ugi=devuser@IP.COM   ip=unknown-ip-addr
>   cmd=get_functions: db=default pat=*
> 18/03/01 11:09:55 INFO Datastore: The class "org.apache.hadoop.hive.metastore.model.MResourceUri"
> is tagged as "embedded-only" so does not have its own datastore table.
> 18/03/01 11:09:55 INFO SessionState: Created local directory:
> /tmp/22ea9ac9-23d1-4247-9e02-ce45809cd9ae_resources
> 18/03/01 11:09:55 INFO SessionState: Created HDFS directory:
> /tmp/hive/hdetldev/22ea9ac9-23d1-4247-9e02-ce45809cd9ae
> 18/03/01 11:09:55 INFO SessionState: Created local directory:
> /tmp/hdetldev/22ea9ac9-23d1-4247-9e02-ce45809cd9ae
> 18/03/01 11:09:55 INFO SessionState: Created HDFS directory:
> /tmp/hive/hdetldev/22ea9ac9-23d1-4247-9e02-ce45809cd9ae/_tmp_space.db
> 18/03/01 11:09:55 INFO HiveContext: default warehouse location is
> /user/hive/warehouse
> 18/03/01 11:09:55 INFO HiveContext: Initializing HiveMetastoreConnection
> version 1.2.1 using Spark classes.
> 18/03/01 11:09:55 INFO ClientWrapper: Inspected Hadoop version:
> 2.7.3.2.6.0.3-8
> 18/03/01 11:09:55 INFO ClientWrapper: Loaded org.apache.hadoop.hive.shims.Hadoop23Shims
> for Hadoop version 2.7.3.2.6.0.3-8
> 18/03/01 11:09:56 INFO metastore: Trying to connect to metastore with URI
> thrift://ip.com:9083
> 18/03/01 11:09:56 INFO metastore: Connected to metastore.
> 18/03/01 11:09:56 INFO SessionState: Created local directory:
> /tmp/24379bb3-8ddf-4716-b68d-07ac0f92d9f1_resources
> 18/03/01 11:09:56 INFO SessionState: Created HDFS directory:
> /tmp/hive/hdetldev/24379bb3-8ddf-4716-b68d-07ac0f92d9f1
> 18/03/01 11:09:56 INFO SessionState: Created local directory:
> /tmp/hdetldev/24379bb3-8ddf-4716-b68d-07ac0f92d9f1
> 18/03/01 11:09:56 INFO SessionState: Created HDFS directory:
> /tmp/hive/hdetldev/24379bb3-8ddf-4716-b68d-07ac0f92d9f1/_tmp_space.db
> 18/03/01 11:09:56 INFO ParseDriver: Parsing command: select count(*) from
> load_etl.trpt_geo_defect_prod_dec07_del_blank
> 18/03/01 11:09:57 INFO ParseDriver: Parse Completed
> 18/03/01 11:09:57 INFO MemoryStore: Block broadcast_0 stored as values in
> memory (estimated size 813.6 KB, free 510.3 MB)
> 18/03/01 11:09:57 INFO MemoryStore: Block broadcast_0_piece0 stored as
> bytes in memory (estimated size 57.5 KB, free 510.3 MB)
> 18/03/01 11:09:57 INFO BlockManagerInfo: Added broadcast_0_piece0 in
> memory on localhost:35508 (size: 57.5 KB, free: 511.1 MB)
> 18/03/01 11:09:57 INFO SparkContext: Created broadcast 0 from showString
> at NativeMethodAccessorImpl.java:-2
> 18/03/01 11:09:58 INFO PerfLogger: <PERFLOG method=OrcGetSplits
> from=org.apache.hadoop.hive.ql.io.orc.ReaderImpl>
> 18/03/01 11:09:58 INFO deprecation: mapred.input.dir is deprecated.
> Instead, use mapreduce.input.fileinputformat.inputdir
> Traceback (most recent call last):
>   File "<stdin>", line 1, in <module>
>   File "/usr/hdp/current/spark-client/python/pyspark/sql/dataframe.py",
> line 257, in show
>     print(self._jdf.showString(n, truncate))
>   File "/var/opt/teradata/anaconda4.1.1/anaconda/lib/python2.7/
> site-packages/py4j-0.10.6-py2.7.egg/py4j/java_gateway.py", line 1160, in
> __call__
>     answer, self.gateway_client, self.target_id, self.name)
>   File "/usr/hdp/current/spark-client/python/pyspark/sql/utils.py", line
> 45, in deco
>     return f(*a, **kw)
>   File "/var/opt/teradata/anaconda4.1.1/anaconda/lib/python2.7/
> site-packages/py4j-0.10.6-py2.7.egg/py4j/protocol.py", line 320, in
> get_return_value
>     format(target_id, ".", name), value)
> py4j.protocol.Py4JJavaError: An error occurred while calling
> o44.showString.
> : org.apache.spark.sql.catalyst.errors.package$TreeNodeException:
> execute, tree:
> TungstenAggregate(key=[], functions=[(count(1),mode=Final,isDistinct=false)],
> output=[_c0#60L])
> +- TungstenExchange SinglePartition, None
>    +- TungstenAggregate(key=[], functions=[(count(1),mode=Partial,isDistinct=false)],
> output=[count#63L])
>       +- HiveTableScan MetastoreRelation load_etl,
> trpt_geo_defect_prod_dec07_del_blank, None
>
>         at org.apache.spark.sql.catalyst.errors.package$.attachTree(
> package.scala:49)
>         at org.apache.spark.sql.execution.aggregate.
> TungstenAggregate.doExecute(TungstenAggregate.scala:80)
>         at org.apache.spark.sql.execution.SparkPlan$$anonfun$
> execute$5.apply(SparkPlan.scala:132)
>         at org.apache.spark.sql.execution.SparkPlan$$anonfun$
> execute$5.apply(SparkPlan.scala:130)
>         at org.apache.spark.rdd.RDDOperationScope$.withScope(
> RDDOperationScope.scala:150)
>         at org.apache.spark.sql.execution.SparkPlan.execute(
> SparkPlan.scala:130)
>         at org.apache.spark.sql.execution.ConvertToSafe.
> doExecute(rowFormatConverters.scala:56)
>         at org.apache.spark.sql.execution.SparkPlan$$anonfun$
> execute$5.apply(SparkPlan.scala:132)
>         at org.apache.spark.sql.execution.SparkPlan$$anonfun$
> execute$5.apply(SparkPlan.scala:130)
>         at org.apache.spark.rdd.RDDOperationScope$.withScope(
> RDDOperationScope.scala:150)
>         at org.apache.spark.sql.execution.SparkPlan.execute(
> SparkPlan.scala:130)
>         at org.apache.spark.sql.execution.SparkPlan.
> executeTake(SparkPlan.scala:187)
>         at org.apache.spark.sql.execution.Limit.
> executeCollect(basicOperators.scala:165)
>         at org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(
> SparkPlan.scala:174)
>         at org.apache.spark.sql.DataFrame$$anonfun$org$apache$
> spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1500)
>         at org.apache.spark.sql.DataFrame$$anonfun$org$apache$
> spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1500)
>         at org.apache.spark.sql.execution.SQLExecution$.
> withNewExecutionId(SQLExecution.scala:56)
>         at org.apache.spark.sql.DataFrame.withNewExecutionId(
> DataFrame.scala:2087)
>         at org.apache.spark.sql.DataFrame.org$apache$spark$
> sql$DataFrame$$execute$1(DataFrame.scala:1499)
>         at org.apache.spark.sql.DataFrame.org$apache$spark$
> sql$DataFrame$$collect(DataFrame.scala:1506)
>         at org.apache.spark.sql.DataFrame$$anonfun$head$1.
> apply(DataFrame.scala:1376)
>         at org.apache.spark.sql.DataFrame$$anonfun$head$1.
> apply(DataFrame.scala:1375)
>         at org.apache.spark.sql.DataFrame.withCallback(
> DataFrame.scala:2100)
>         at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1375)
>         at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1457)
>         at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:170)
>         at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>         at sun.reflect.NativeMethodAccessorImpl.invoke(
> NativeMethodAccessorImpl.java:62)
>         at sun.reflect.DelegatingMethodAccessorImpl.invoke(
> DelegatingMethodAccessorImpl.java:43)
>         at java.lang.reflect.Method.invoke(Method.java:498)
>         at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
>         at py4j.reflection.ReflectionEngine.invoke(
> ReflectionEngine.java:381)
>         at py4j.Gateway.invoke(Gateway.java:259)
>         at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.
> java:133)
>         at py4j.commands.CallCommand.execute(CallCommand.java:79)
>         at py4j.GatewayConnection.run(GatewayConnection.java:209)
>         at java.lang.Thread.run(Thread.java:748)
> Caused by: org.apache.spark.sql.catalyst.errors.package$TreeNodeException:
> execute, tree:
> TungstenExchange SinglePartition, None
> +- TungstenAggregate(key=[], functions=[(count(1),mode=Partial,isDistinct=false)],
> output=[count#63L])
>    +- HiveTableScan MetastoreRelation load_etl, trpt_geo_defect_prod_dec07_del_blank,
> None
>
>         at org.apache.spark.sql.catalyst.errors.package$.attachTree(
> package.scala:49)
>         at org.apache.spark.sql.execution.Exchange.doExecute(
> Exchange.scala:247)
>         at org.apache.spark.sql.execution.SparkPlan$$anonfun$
> execute$5.apply(SparkPlan.scala:132)
>         at org.apache.spark.sql.execution.SparkPlan$$anonfun$
> execute$5.apply(SparkPlan.scala:130)
>         at org.apache.spark.rdd.RDDOperationScope$.withScope(
> RDDOperationScope.scala:150)
>         at org.apache.spark.sql.execution.SparkPlan.execute(
> SparkPlan.scala:130)
>         at org.apache.spark.sql.execution.aggregate.
> TungstenAggregate$$anonfun$doExecute$1.apply(TungstenAggregate.scala:86)
>         at org.apache.spark.sql.execution.aggregate.
> TungstenAggregate$$anonfun$doExecute$1.apply(TungstenAggregate.scala:80)
>         at org.apache.spark.sql.catalyst.errors.package$.attachTree(
> package.scala:48)
>         ... 36 more
> Caused by: java.lang.RuntimeException: serious problem
>         at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.
> generateSplitsInfo(OrcInputFormat.java:1021)
>         at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.getSplits(
> OrcInputFormat.java:1048)
>         at org.apache.spark.rdd.HadoopRDD.getPartitions(
> HadoopRDD.scala:202)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:242)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:240)
>         at scala.Option.getOrElse(Option.scala:120)
>         at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
>         at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(
> MapPartitionsRDD.scala:35)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:242)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:240)
>         at scala.Option.getOrElse(Option.scala:120)
>         at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
>         at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(
> MapPartitionsRDD.scala:35)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:242)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:240)
>         at scala.Option.getOrElse(Option.scala:120)
>         at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
>         at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(
> MapPartitionsRDD.scala:35)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:242)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:240)
>         at scala.Option.getOrElse(Option.scala:120)
>         at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
>         at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(
> MapPartitionsRDD.scala:35)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:242)
>         at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(
> RDD.scala:240)
>         at scala.Option.getOrElse(Option.scala:120)
>         at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
>         at org.apache.spark.ShuffleDependency.<init>(Dependency.scala:91)
>         at org.apache.spark.sql.execution.Exchange.
> prepareShuffleDependency(Exchange.scala:220)
>         at org.apache.spark.sql.execution.Exchange$$anonfun$
> doExecute$1.apply(Exchange.scala:254)
>         at org.apache.spark.sql.execution.Exchange$$anonfun$
> doExecute$1.apply(Exchange.scala:248)
>         at org.apache.spark.sql.catalyst.errors.package$.attachTree(
> package.scala:48)
>         ... 44 more
> Caused by: java.util.concurrent.ExecutionException: java.lang.NumberFormatException:
> For input string: "0003024_0000"
>         at java.util.concurrent.FutureTask.report(FutureTask.java:122)
>         at java.util.concurrent.FutureTask.get(FutureTask.java:192)
>         at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.
> generateSplitsInfo(OrcInputFormat.java:998)
>         ... 75 more
> Caused by: java.lang.NumberFormatException: For input string:
> "0003024_0000"
>         at java.lang.NumberFormatException.forInputString(
> NumberFormatException.java:65)
>         at java.lang.Long.parseLong(Long.java:589)
>         at java.lang.Long.parseLong(Long.java:631)
>         at org.apache.hadoop.hive.ql.io.AcidUtils.parseDelta(
> AcidUtils.java:310)
>         at org.apache.hadoop.hive.ql.io.AcidUtils.getAcidState(
> AcidUtils.java:379)
>         at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$
> FileGenerator.call(OrcInputFormat.java:634)
>         at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$
> FileGenerator.call(OrcInputFormat.java:620)
>         at java.util.concurrent.FutureTask.run(FutureTask.java:266)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(
> ThreadPoolExecutor.java:1149)
>         at java.util.concurrent.ThreadPoolExecutor$Worker.run(
> ThreadPoolExecutor.java:624)
>         ... 1 more
>
>
>
>
>
>
>
>
> Here is the detail of the table creation:
>
>
>
> Transaction isolation: TRANSACTION_REPEATABLE_READ
> Beeline version 1.2.1000.2.6.0.3-8 by Apache Hive
> 0: jdbc:hive2://toplxhdmd001.rights.com> show create table
> load_etl.trpt_geo_defect_prod_dec07_del_blank;
> +-----------------------------------------------------------
> ------------------------------------+--+
> |                                        createtab_stmt
>                      |
> +-----------------------------------------------------------
> ------------------------------------+--+
> | CREATE TABLE `load_etl.trpt_geo_defect_prod_dec07_del_blank`(
>                        |
> |   `line_seg_nbr` int,
>                      |
> |   `track_type` string,
>                       |
> |   `track_sdtk_nbr` string,
>                       |
> |   `mile_post_beg` double,
>                      |
> |   `ss_nbr` int,
>                      |
> |   `ss_len` int,
>                      |
> |   `ris1mpb` double,
>                      |
> |   `mile_label` string,
>                       |
> |   `test_dt` string,
>                      |
> |   `def_prty` string,
>                       |
> |   `def_nbr` int,
>                       |
> |   `def_type` string,
>                       |
> |   `def_ampltd` double,
>                       |
> |   `def_lgth` int,
>                      |
> |   `car_cd` string,
>                       |
> |   `tsc_cd` string,
>                       |
> |   `class` string,
>                      |
> |   `test_fspd` string,
>                      |
> |   `test_pspd` string,
>                      |
> |   `restr_fspd` string,
>                       |
> |   `restr_pspd` string,
>                     |
> |   `def_land_mark` string,
>                      |
> |   `repeat_cd` string,
>                      |
> |   `mp_incr_cd` string,
>                       |
> |   `test_trk_dir` string,
>                       |
> |   `eff_dt` string,
>                       |
> |   `trk_file` string,
>                       |
> |   `dfct_cor_dt` string,
>                      |
> |   `dfct_acvt` string,
>                      |
> |   `dfct_slw_ord_ind` string,
>                       |
> |   `emp_id` string,
>                       |
> |   `eff_ts` string,
>                       |
> |   `dfct_cor_tm` string,
>                      |
> |   `dfct_freight_spd` int,
>                      |
> |   `dfct_amtrak_spd` int,
>                       |
> |   `mile_post_sfx` string,
>                      |
> |   `work_order_id` string,
>                      |
> |   `loc_id_beg` string,
>                       |
> |   `loc_id_end` string,
>                       |
> |   `link_id` string,
>                      |
> |   `lst_maint_ts` string,
>                       |
> |   `del_ts` string,
>                       |
> |   `gps_longitude` double,
>                      |
> |   `gps_latitude` double,
>                       |
> |   `geo_car_nme` string,
>                      |
> |   `rept_gc_nme` string,
>                      |
> |   `rept_dfct_tst` string,
>                      |
> |   `rept_dfct_nbr` int,
>                       |
> |   `restr_trk_cls` string,
>                      |
> |   `tst_hist_cd` string,
>                      |
> |   `cret_ts` string,
>                      |
> |   `ylw_grp_nbr` int,
>                       |
> |   `geo_dfct_grp_nme` string,
>                       |
> |   `supv_rollup_cd` string,
>                       |
> |   `dfct_stat_cd` string,
>                       |
> |   `lst_maint_id` string,
>                       |
> |   `del_rsn_cd` string,
>                       |
> |   `umt_prcs_user_id` string,
>                       |
> |   `gdfct_vinsp_srestr` string,
>                       |
> |   `gc_opr_init` string)
>                      |
> | CLUSTERED BY (
>                       |
> |   geo_car_nme)
>                       |
> | INTO 2 BUCKETS
>                       |
> | ROW FORMAT SERDE
>                       |
> |   'org.apache.hadoop.hive.ql.io.orc.OrcSerde'
>                        |
> | STORED AS INPUTFORMAT
>                      |
> |   'org.apache.hadoop.hive.ql.io.orc.OrcInputFormat'
>                        |
> | OUTPUTFORMAT
>                       |
> |   'org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat'
>                       |
> | LOCATION
>                       |
> |   'hdfs://HADOOP02/apps/hive/warehouse/load_etl.db/trpt_
> geo_defect_prod_dec07_del_blank'  |
> | TBLPROPERTIES (
>                      |
> |   'numFiles'='4',
>                      |
> |   'numRows'='0',
>                       |
> |   'rawDataSize'='0',
>                       |
> |   'totalSize'='2566942',
>                       |
> |   'transactional'='true',
>                      |
> |   'transient_lastDdlTime'='1518695199')
>                        |
> +-----------------------------------------------------------
> ------------------------------------+--+
>
>
> Thanks,
> D
>



-- 
Best Regards,
Ayan Guha

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