Member since
02-06-2017
20
Posts
4
Kudos Received
2
Solutions
My Accepted Solutions
Title | Views | Posted |
---|---|---|
22937 | 08-05-2018 07:38 AM | |
4190 | 06-12-2016 05:15 PM |
06-07-2019
03:34 PM
i really love hdp especially ambari . could somebody answer my question since i noticed no more new hdp release for a while.
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Hortonworks Data Platform (HDP)
01-11-2019
07:11 PM
my final solution is install hbase and my the real base as storage for both ats and ambari metrics .error cleared
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01-08-2019
12:36 AM
hi Geoffrey, I tried by the problem still there .though it's not a big problem for my yarn application .
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01-07-2019
09:40 PM
same thing here ,even after restart everything the "The HBase application reported a 'STARTED' state" is there.
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08-05-2018
07:38 AM
1 Kudo
hi Aditya, Thank you for the response . The issue was related to when using spark to write to hive ,now have to provide the table format as below df.write.format("orc").mode("overwrite").saveAsTable("tt") # this run good
df.write.mode("overwrite").saveAsTable("tt") # this command will fail I didn't change anything on hive tab after hdp 3.0 installed .
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08-03-2018
09:19 PM
Hi ,just doing some testing on newly posted hdp 3.0. and the example failed . I tested same script on previous HDP platform, works fine. can someone advice it's hive's new feature or anything I have done wrong? ./bin/spark-submit examples/src/main/python/sql/hive.py
Hive Session ID = bf71304b-3435-46d5-93a9-09ef752b6c22
AnalysisExceptionTraceback (most recent call last)
/usr/hdp/3.0.0.0-1634/spark2/examples/src/main/python/sql/hive.py in <module>()
44
45 # spark is an existing SparkSession
46 spark.sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING) USING hive")
47 spark.sql("LOAD DATA LOCAL INPATH 'examples/src/main/resources/kv1.txt' INTO TABLE src")
48
/usr/hdp/3.0.0.0-1634/spark2/python/lib/pyspark.zip/pyspark/sql/session.py in sql(self, sqlQuery)
714 [Row(f1=1, f2=u'row1'), Row(f1=2, f2=u'row2'), Row(f1=3, f2=u'row3')]
715 """
716 return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)
717
718 @since(2.0)
/usr/hdp/3.0.0.0-1634/spark2/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py in __call__(self, *args)
1255 answer = self.gateway_client.send_command(command)
1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
1258
1259 for temp_arg in temp_args:
/usr/hdp/3.0.0.0-1634/spark2/python/lib/pyspark.zip/pyspark/sql/utils.py in deco(*a, **kw)
67 e.java_exception.getStackTrace()))
68 if s.startswith('org.apache.spark.sql.AnalysisException: '):
69 raise AnalysisException(s.split(': ', 1)[1], stackTrace)
70 if s.startswith('org.apache.spark.sql.catalyst.analysis'):
71 raise AnalysisException(s.split(': ', 1)[1], stackTrace) AnalysisException: u'org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:Table default.src failed strict managed table checks due to the following reason:
Table is marked as a managed table but is not transactional.);' much appreciated!
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07-07-2018
02:16 PM
thank you very much ,that' my bad ,I had added some other jars in my class path leading to this error.
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07-07-2018
04:27 AM
Hi ,
I'm using latest HDP ,version is 2.6.5.0-292. spark version is 2.3.0
when I'm trying to run show() from any DataFrame ,it always throw error :
scala> spark.read.csv("/user/a.txt").show() java.lang.NoSuchMethodError: net.jpountz.lz4.LZ4BlockInputStream.<init>(Ljava/io/InputStream;Z)V
at org.apache.spark.io.LZ4CompressionCodec.compressedInputStream(CompressionCodec.scala:122)
at org.apache.spark.sql.execution.SparkPlan.org$apache$spark$sql$execution$SparkPlan$decodeUnsafeRows(SparkPlan.scala:274)
at org.apache.spark.sql.execution.SparkPlan$anonfun$executeTake$1.apply(SparkPlan.scala:366)
at org.apache.spark.sql.execution.SparkPlan$anonfun$executeTake$1.apply(SparkPlan.scala:366)
at scala.collection.TraversableLike$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.mutable.ArrayOps$ofRef.flatMap(ArrayOps.scala:186)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:366)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$collectFromPlan(Dataset.scala:3272)
at org.apache.spark.sql.Dataset$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$anonfun$head$1.apply(Dataset.scala:2484)
at org.apache.spark.sql.Dataset$anonfun$52.apply(Dataset.scala:3253)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.infer(CSVDataSource.scala:148)
at org.apache.spark.sql.execution.datasources.csv.CSVDataSource.inferSchema(CSVDataSource.scala:63)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat.inferSchema(CSVFileFormat.scala:57)
at org.apache.spark.sql.execution.datasources.DataSource$anonfun$8.apply(DataSource.scala:202)
at org.apache.spark.sql.execution.datasources.DataSource$anonfun$8.apply(DataSource.scala:202)
at scala.Option.orElse(Option.scala:289)
at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:201)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:392)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:596)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:473)
I've tried both pyspark and spark-shell on 3 sets of newly installed hdp 2.6.5.0-292. the DataFrame writing function works well ,only show() throws the error. are there anyone encountered same issue as I had? how to fix this problem?
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Hortonworks Data Platform (HDP)
11-19-2017
01:15 AM
this is really great I think the key point here is as -Dhdp.version it's is still working for hdp version 2.6.3.0-235
spark.driver.extraJavaOptions -Dhdp.version=2.5.0.0-817 spark.yarn.am.extraJavaOptions -Dhdp.version=2.5.0.0-817
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06-12-2016
06:43 PM
Just checked the pom.xml file for phoenix 4.7 ,it's based on hadoop 2.5.1 which the container id should looks like container_1465095377475_0007_02_000001, while in hadoop 2.7.1 the container id should looks like container_e03_1465095377475_0007_02_000001. So the old version of class org.apache.hadoop.yarn.util.ConverterUtils.toContainerId couldn't handle the new version's container . I should address this problem in phoenix comminity either.
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