Spark2 unable to find table or view on remote hdfs cluster - scala

Question

I am using HiveContext to query a hive table on a hdfs cluster remotely through spark 1.6.0 and am able to do so successfully. However, when doing so through spark 2.3.0, throws the following:
org.apache.spark.sql.AnalysisException:
Table or view not found: `hiveorc_replica`.`appointment`; line 1 pos 21;
'Aggregate [unresolvedalias(count(1), None)]
+- 'UnresolvedRelation `hiveorc_replica`.`appointment`
Through this message, I am able to interpret only one thing that it might be searching for the database locally instead of remotely. I am creating a spark context using:
val conf = new SparkConf().setAppName("SparkApp").setMaster("local")
val sc=new SparkContext(conf)
val hc = new HiveContext(sc)
val actualRecordCountHC = hc.sql("select count(*) from hiveorc_replica.appointment")
val records = hc.sql("select * from hiveorc_replica.appointment")
All the config files are present in the resources folder of my project. The following is my hive-site.xml:
<?xml version="1.0" encoding="UTF-8"?>
<!--Autogenerated by Cloudera Manager-->
<configuration>
<property>
<name>hive.metastore.uris</name>
<value>thrift://fqdn:9083</value>
</property>
<property>
<name>hive.metastore.client.socket.timeout</name>
<value>300</value>
</property>
<property>
<name>hive.metastore.warehouse.dir</name>
<value>/user/hive/warehouse</value>
</property>
<property>
<name>hive.warehouse.subdir.inherit.perms</name>
<value>true</value>
</property>
<property>
<name>hive.auto.convert.join</name>
<value>true</value>
</property>
<property>
<name>hive.auto.convert.join.noconditionaltask.size</name>
<value>20971520</value>
</property>
<property>
<name>hive.optimize.bucketmapjoin.sortedmerge</name>
<value>false</value>
</property>
<property>
<name>hive.smbjoin.cache.rows</name>
<value>10000</value>
</property>
<property>
<name>hive.server2.logging.operation.enabled</name>
<value>true</value>
</property>
<property>
<name>hive.server2.logging.operation.log.location</name>
<value>/var/log/hive/operation_logs</value>
</property>
<property>
<name>mapred.reduce.tasks</name>
<value>-1</value>
</property>
<property>
<name>hive.exec.reducers.bytes.per.reducer</name>
<value>67108864</value>
</property>
<property>
<name>hive.exec.copyfile.maxsize</name>
<value>33554432</value>
</property>
<property>
<name>hive.exec.reducers.max</name>
<value>1099</value>
</property>
<property>
<name>hive.vectorized.groupby.checkinterval</name>
<value>4096</value>
</property>
<property>
<name>hive.vectorized.groupby.flush.percent</name>
<value>0.1</value>
</property>
<property>
<name>hive.compute.query.using.stats</name>
<value>false</value>
</property>
<property>
<name>hive.vectorized.execution.enabled</name>
<value>false</value>
</property>
<property>
<name>hive.vectorized.execution.reduce.enabled</name>
<value>false</value>
</property>
<property>
<name>hive.merge.mapfiles</name>
<value>true</value>
</property>
<property>
<name>hive.merge.mapredfiles</name>
<value>false</value>
</property>
<property>
<name>hive.cbo.enable</name>
<value>false</value>
</property>
<property>
<name>hive.fetch.task.conversion</name>
<value>minimal</value>
</property>
<property>
<name>hive.fetch.task.conversion.threshold</name>
<value>268435456</value>
</property>
<property>
<name>hive.limit.pushdown.memory.usage</name>
<value>0.1</value>
</property>
<property>
<name>hive.merge.sparkfiles</name>
<value>true</value>
</property>
<property>
<name>hive.merge.smallfiles.avgsize</name>
<value>16777216</value>
</property>
<property>
<name>hive.merge.size.per.task</name>
<value>268435456</value>
</property>
<property>
<name>hive.optimize.reducededuplication</name>
<value>true</value>
</property>
<property>
<name>hive.optimize.reducededuplication.min.reducer</name>
<value>4</value>
</property>
<property>
<name>hive.map.aggr</name>
<value>true</value>
</property>
<property>
<name>hive.map.aggr.hash.percentmemory</name>
<value>0.5</value>
</property>
<property>
<name>hive.optimize.sort.dynamic.partition</name>
<value>false</value>
</property>
<property>
<name>hive.execution.engine</name>
<value>mr</value>
</property>
<property>
<name>spark.executor.memory</name>
<value>268435456</value>
</property>
<property>
<name>spark.driver.memory</name>
<value>268435456</value>
</property>
<property>
<name>spark.executor.cores</name>
<value>1</value>
</property>
<property>
<name>spark.yarn.driver.memoryOverhead</name>
<value>26</value>
</property>
<property>
<name>spark.yarn.executor.memoryOverhead</name>
<value>26</value>
</property>
<property>
<name>spark.dynamicAllocation.enabled</name>
<value>true</value>
</property>
<property>
<name>spark.dynamicAllocation.initialExecutors</name>
<value>1</value>
</property>
<property>
<name>spark.dynamicAllocation.minExecutors</name>
<value>1</value>
</property>
<property>
<name>spark.dynamicAllocation.maxExecutors</name>
<value>2147483647</value>
</property>
<property>
<name>hive.metastore.execute.setugi</name>
<value>true</value>
</property>
<property>
<name>hive.support.concurrency</name>
<value>true</value>
</property>
<property>
<name>hive.zookeeper.quorum</name>
<value>fqdn</value>
</property>
<property>
<name>hive.zookeeper.client.port</name>
<value>2181</value>
</property>
<property>
<name>hive.zookeeper.namespace</name>
<value>hive_zookeeper_namespace_CD-HIVE-WAyDdBlP</value>
</property>
<property>
<name>hive.cluster.delegation.token.store.class</name>
<value>org.apache.hadoop.hive.thrift.MemoryTokenStore</value>
</property>
<property>
<name>hive.server2.enable.doAs</name>
<value>true</value>
</property>
<property>
<name>hive.metastore.sasl.enabled</name>
<value>true</value>
</property>
<property>
<name>hive.metastore.kerberos.principal</name>
<value>hive/_HOST#EXAMPLE.COM</value>
</property>
<property>
<name>hive.server2.authentication.kerberos.principal</name>
<value>hive/_HOST#EXAMPLE.COM</value>
</property>
<property>
<name>spark.shuffle.service.enabled</name>
<value>true</value>
</property>
<property>
<name>hive.server2.authentication</name>
<value>LDAP</value>
</property>
</configuration>
fqdn is being replaced by remote hdfs FQDN at runtime. Also, when I run the same code on the remote cluster itself where the hive database is present, through spark2, it gives results.
So, how do i run the code remotely ?

Answer 1

creating spark session for spark2 did the job. On seeing the logs, I found that somehow it was unable to get the value of hive.metastore.uris from hive-site.xml and setting it through spark-session was the answer.
val spark = SparkSession.builder.master("local").config("hive.metastore.uris", "thrift://"+hdfsFQDN+":9083").enableHiveSupport.getOrCreate
However, I still have a doubt as to why is it not able to get value of hive.metastore.uri for running remotely when its able to get the file from resources when running through HiveContext ?