That's understandable. Maybe I can help. :)
What happens if you set `HIVE_TABLE_NAME = "default.employees"`?
Also, does that table exist before you call
`filtered_output_timestamp.write.mode("append").saveAsTable(HIVE_TABLE_NAME)`?
Cheers,
Michael
> On Jan 29, 2017, at 9:52 PM, Chetan Khatri <chetan.opensou...@gmail.com>
> wrote:
>
> Okey, you are saying that 2.0.0 don't have that patch fixed ? @dev cc--
> I don't like everytime changing the service versions !
>
> Thanks.
>
> On Mon, Jan 30, 2017 at 1:10 AM, Jacek Laskowski <ja...@japila.pl
> <mailto:ja...@japila.pl>> wrote:
> Hi,
>
> I think you have to upgrade to 2.1.0. There were few changes wrt the ERROR
> since.
>
> Jacek
>
>
> On 29 Jan 2017 9:24 a.m., "Chetan Khatri" <chetan.opensou...@gmail.com
> <mailto:chetan.opensou...@gmail.com>> wrote:
> Hello Spark Users,
>
> I am getting error while saving Spark Dataframe to Hive Table:
> Hive 1.2.1
> Spark 2.0.0
> Local environment.
> Note: Job is getting executed successfully and the way I want but still
> Exception raised.
> Source Code:
>
> package com.chetan.poc.hbase
>
> /**
> * Created by chetan on 24/1/17.
> */
> import org.apache.hadoop.hbase.{CellUtil, HBaseConfiguration}
> import org.apache.hadoop.hbase.mapreduce.TableInputFormat
> import org.apache.hadoop.hbase.util.Bytes
> import org.apache.hadoop.hbase.KeyValue.Type
> import org.apache.spark.sql.SparkSession
> import scala.collection.JavaConverters._
> import java.util.Date
> import java.text.SimpleDateFormat
>
>
> object IncrementalJob {
> val APP_NAME: String = "SparkHbaseJob"
> var HBASE_DB_HOST: String = null
> var HBASE_TABLE: String = null
> var HBASE_COLUMN_FAMILY: String = null
> var HIVE_DATA_WAREHOUSE: String = null
> var HIVE_TABLE_NAME: String = null
> def main(args: Array[String]) {
> // Initializing HBASE Configuration variables
> HBASE_DB_HOST="127.0.0.1"
> HBASE_TABLE="university"
> HBASE_COLUMN_FAMILY="emp"
> // Initializing Hive Metastore configuration
> HIVE_DATA_WAREHOUSE = "/usr/local/hive/warehouse"
> // Initializing Hive table name - Target table
> HIVE_TABLE_NAME = "employees"
> // setting spark application
> // val sparkConf = new SparkConf().setAppName(APP_NAME).setMaster("local")
> //initialize the spark context
> //val sparkContext = new SparkContext(sparkConf)
> //val sqlContext = new org.apache.spark.sql.SQLContext(sparkContext)
> // Enable Hive with Hive warehouse in SparkSession
> val spark =
> SparkSession.builder().appName(APP_NAME).config("hive.metastore.warehouse.dir",
> HIVE_DATA_WAREHOUSE).config("spark.sql.warehouse.dir",
> HIVE_DATA_WAREHOUSE).enableHiveSupport().getOrCreate()
> import spark.implicits._
> import spark.sql
>
> val conf = HBaseConfiguration.create()
> conf.set(TableInputFormat.INPUT_TABLE, HBASE_TABLE)
> conf.set(TableInputFormat.SCAN_COLUMNS, HBASE_COLUMN_FAMILY)
> // Load an RDD of rowkey, result(ImmutableBytesWritable, Result) tuples
> from the table
> val hBaseRDD = spark.sparkContext.newAPIHadoopRDD(conf,
> classOf[TableInputFormat],
> classOf[org.apache.hadoop.hbase.io
> <http://hbase.io/>.ImmutableBytesWritable],
> classOf[org.apache.hadoop.hbase.client.Result])
>
> println(hBaseRDD.count())
> //hBaseRDD.foreach(println)
>
> //keyValue is a RDD[java.util.list[hbase.KeyValue]]
> val keyValue = hBaseRDD.map(x => x._2).map(_.list)
>
> //outPut is a RDD[String], in which each line represents a record in HBase
> val outPut = keyValue.flatMap(x => x.asScala.map(cell =>
>
> HBaseResult(
> Bytes.toInt(CellUtil.cloneRow(cell)),
> Bytes.toStringBinary(CellUtil.cloneFamily(cell)),
> Bytes.toStringBinary(CellUtil.cloneQualifier(cell)),
> cell.getTimestamp,
> new SimpleDateFormat("yyyy-MM-dd HH:mm:ss:SSS").format(new
> Date(cell.getTimestamp.toLong)),
> Bytes.toStringBinary(CellUtil.cloneValue(cell)),
> Type.codeToType(cell.getTypeByte).toString
> )
> )
> ).toDF()
> // Output dataframe
> outPut.show
>
> // get timestamp
> val datetimestamp_threshold = "2016-08-25 14:27:02:001"
> val datetimestampformat = new SimpleDateFormat("yyyy-MM-dd
> HH:mm:ss:SSS").parse(datetimestamp_threshold).getTime()
>
> // Resultset filteration based on timestamp
> val filtered_output_timestamp = outPut.filter($"colDatetime" >=
> datetimestampformat)
> // Resultset filteration based on rowkey
> val filtered_output_row =
> outPut.filter($"colDatetime".between(1668493360,1668493365))
>
>
> // Saving Dataframe to Hive Table Successfully.
>
> filtered_output_timestamp.write.mode("append").saveAsTable(HIVE_TABLE_NAME)
> }
> case class HBaseResult(rowkey: Int, colFamily: String, colQualifier:
> String, colDatetime: Long, colDatetimeStr: String, colValue: String, colType:
> String)
> }
>
> Error:
> 17/01/29 13:51:53 INFO metastore.HiveMetaStore: 0: create_database:
> Database(name:default, description:default database,
> locationUri:hdfs://localhost:9000/usr/local/hive/warehouse, parameters:{})
> 17/01/29 13:51:53 INFO HiveMetaStore.audit: ugi=hduser
> ip=unknown-ip-addr cmd=create_database: Database(name:default,
> description:default database,
> locationUri:hdfs://localhost:9000/usr/local/hive/warehouse, parameters:{})
> 17/01/29 13:51:53 ERROR metastore.RetryingHMSHandler:
> AlreadyExistsException(message:Database default already exists)
> at
> org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.create_database(HiveMetaStore.java:891)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.hadoop.hive.metastore.RetryingHMSHandler.invoke(RetryingHMSHandler.java:107)
> at com.sun.proxy.$Proxy21.create_database(Unknown Source)
> at
> org.apache.hadoop.hive.metastore.HiveMetaStoreClient.createDatabase(HiveMetaStoreClient.java:644)
> 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.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:156)
> at com.sun.proxy.$Proxy22.createDatabase(Unknown Source)
> at org.apache.hadoop.hive.ql.metadata.Hive.createDatabase(Hive.java:306)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$createDatabase$1.apply$mcV$sp(HiveClientImpl.scala:309)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$createDatabase$1.apply(HiveClientImpl.scala:309)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$createDatabase$1.apply(HiveClientImpl.scala:309)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:280)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:227)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:226)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:269)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.createDatabase(HiveClientImpl.scala:308)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$createDatabase$1.apply$mcV$sp(HiveExternalCatalog.scala:99)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$createDatabase$1.apply(HiveExternalCatalog.scala:99)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$createDatabase$1.apply(HiveExternalCatalog.scala:99)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:72)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.createDatabase(HiveExternalCatalog.scala:98)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.createDatabase(SessionCatalog.scala:147)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.<init>(SessionCatalog.scala:89)
> at
> org.apache.spark.sql.hive.HiveSessionCatalog.<init>(HiveSessionCatalog.scala:51)
> at
> org.apache.spark.sql.hive.HiveSessionState.catalog$lzycompute(HiveSessionState.scala:49)
> at
> org.apache.spark.sql.hive.HiveSessionState.catalog(HiveSessionState.scala:48)
> at
> org.apache.spark.sql.hive.HiveSessionState$$anon$1.<init>(HiveSessionState.scala:63)
> at
> org.apache.spark.sql.hive.HiveSessionState.analyzer$lzycompute(HiveSessionState.scala:63)
> at
> org.apache.spark.sql.hive.HiveSessionState.analyzer(HiveSessionState.scala:62)
> at
> org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:161)
> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:167)
> at org.apache.spark.sql.Dataset$.apply(Dataset.scala:59)
> at
> org.apache.spark.sql.SparkSession.createDataset(SparkSession.scala:441)
> at org.apache.spark.sql.SQLContext.createDataset(SQLContext.scala:395)
> at
> org.apache.spark.sql.SQLImplicits.rddToDatasetHolder(SQLImplicits.scala:163)
> at com.chetan.poc.hbase.IncrementalJob$.main(IncrementalJob.scala:58)
> at com.chetan.poc.hbase.IncrementalJob.main(IncrementalJob.scala)
> 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.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:736)
> at
> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>
>
> Thanks.
>
>
