We are facing some challenges working with spark and hive.
We need to connect to hive-metastore from spark and we have to use custom hive-metastore-client inside spark.
code snippet:
spark = SparkSession \
.builder \
.config('spark.sql.hive.metastore.version','3.1.2' ) \
.config('spark.sql.hive.metastore.jars', 'hive-standalone-metastore-3.1.2-sqlquery.jar') \
.config("spark.yarn.dist.jars", "hive-exec-3.1.2.jar") \
.config('hive.metastore.uris', "thrift://localhost:9090") \
the above code works with inbuilt hive-metastore-client but fails with custom one with error:
py4j.protocol.Py4JJavaError: An error occurred while calling o79.databaseExists.
: java.lang.NoClassDefFoundError: org/apache/hadoop/hive/ql/metadata/HiveException
Caused by: java.lang.ClassNotFoundException: org.apache.hadoop.hive.ql.metadata.HiveException
To resolve this issue, we have configured custom hive-exec in code and also tried to pass using command line:
/usr/local/Cellar/apache-spark/3.1.2/libexec/bin/spark-submit spark-session.py --jars hive-exec-3.1.2.jar
/usr/local/Cellar/apache-spark/3.1.2/libexec/bin/spark-submit spark-session.py --conf spark.executor.extraClassPath hive-exec-3.1.2.jar
/usr/local/Cellar/apache-spark/3.1.2/libexec/bin/spark-submit spark-session.py --driver-class-path hive-exec-3.1.2.jar
But the issue is not resolved yet, any suggestion would help us.
Related
I am trying to load google patent data using bigquery with the following code (Python).
df= spark.read \ .format("bigquery") \ .option("table", table) \ .option("filter", "country_code = '{}' AND application_kind = '{}' AND publication_date >= {} AND publication_date < {}".format(country, kind, date_from, date_to)) \ .load()
Then I got the following error that says
Py4JJavaError: An error occurred while calling o144.load. : java.lang.ClassNotFoundException: Failed to find data source: bigquery. Please find packages at http://spark.apache.org/third-party-projects.html
I am suspecting the cause for this error is the lack of bigquery package in my cluster (I checked it on the configuration). I tried to add bigquery using gcp shell command. I get an error of,
$ gcloud dataproc jobs submit spark \ --cluster=my-cluster\ --region=europe-west2 \ --jar=gs://spark-lib/bigquery/spark-bigquery-latest_2.12.jar
But I got an error again
Exception in thread "main" org.apache.spark.SparkException: Failed to get main class in JAR with error 'null'. Please specify one with --class.
How do I install (gcloud dataproc jobs submit spark) bigquery??? Ideally on dataproc.
I don't know what to add in terms of --class
I'm trying to retrieve data from MariaDB with pyspark.
I created spark_session with configuration to include jdbc jar file, but couldn't solve problem. Current code to create session looks like below.
path = "hdfs://nameservice1/user/PATH/TO/JDBC/mariadb-java-client-2.7.1.jar"
# or path = "/home/PATH/TO/JDBC/mariadb-java-client-2.7.1.jar"
spark = SparkSession.config("spark.jars", path)\
.config("spark.driver.extraClassPath", path)\
.config("spark.executor.extraClassPath", path)\
.enableHiveSupport()
.getOrCreate()
Note that I've tried every case of configuration I know
(Check Permission, change directory both hdfs or local, add or remove configuration ...)
And then, code to load data is.
sql = "SOME_SQL_TO_RETRIEVE_DATA"
spark = spark.read.format('jdbc').option('dbtable', sql)
.option('url', 'jdbc:mariadb://{host}:{port}/{db}')\
.option("user", SOME_USER)
.option("password", SOME_PASSWORD)
.option("driver", 'org.mariadb.jdbc.Driver')
.load()
But it fails with java.lang.ClassNotFoundException: org.mariadb.jdbc.Driver
When I tried this with spark-submit, I saw log message.
... INFO SparkContext: Added Jar /PATH/TO/JDBC/mariadb-java-client-2.7.1.jar at spark://SOME_PATH/jars/mariadb-java-client-2.7.1.jar with timestamp SOME_TIMESTAMP
What is wrong?
For anyone who suffers from same problem.
I figured out. Spark Document says that
Note: In client mode, this config must not be set through the SparkConf directly in your application, because the driver JVM has already started at that point. Instead, please set this through the --driver-class-path command line option or in your default properties file.
So instead setting configuration on python code, I added arguments on spark-submit following this document.
spark-submit {other arguments ...} \
--driver-class-path PATH/TO/JDBC/my-jdbc.jar \
--jars PATH/TO/JDBC/my-jdbc.jar \
MY_PYTHON_SCRIPT.py
unable to write the data into hive using pyspark through jupyter notebook .
giving me below error
Py4JJavaError: An error occurred while calling o99.saveAsTable.
: org.apache.spark.sql.AnalysisException: java.lang.RuntimeException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient;
Note these steps already tried:
copied the hdfs-site.xml , core-site.xml to /conf of hive
removed metasotore_db and created again using below cmd
$HIVE_HOME/bin/schematool –initschema –dbtype derby
did you use spark-submit for running your script?
Also you should add -> ".enableHiveSupport()" like that:
spark = SparkSession.builder \
.appName("yourapp") \
.enableHiveSupport() \
.getOrCreate()
I am trying to run my spark code from jupyter notebook to my company server.
So i add the following code
spark = SparkSession.builder.master("spark://host:port") \
.appName("usres information analysis") \
.config("spark.executor.memory","5g") \
.getOrCreate()
in my notebook. But i am getting the following error
An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.
: java.lang.NullPointerException
Is there any problem with my code?
I have the following as the command line to start a spark streaming job.
spark-submit --class com.biz.test \
--packages \
org.apache.spark:spark-streaming-kafka_2.10:1.3.0 \
org.apache.hbase:hbase-common:1.0.0 \
org.apache.hbase:hbase-client:1.0.0 \
org.apache.hbase:hbase-server:1.0.0 \
org.json4s:json4s-jackson:3.2.11 \
./test-spark_2.10-1.0.8.jar \
>spark_log 2>&1 &
The job fails to start with the following error:
Exception in thread "main" java.lang.IllegalArgumentException: Given path is malformed: org.apache.hbase:hbase-common:1.0.0
at org.apache.spark.util.Utils$.resolveURI(Utils.scala:1665)
at org.apache.spark.deploy.SparkSubmitArguments.parse$1(SparkSubmitArguments.scala:432)
at org.apache.spark.deploy.SparkSubmitArguments.parseOpts(SparkSubmitArguments.scala:288)
at org.apache.spark.deploy.SparkSubmitArguments.<init>(SparkSubmitArguments.scala:87)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:105)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
I've tried removing the formatting and returning to a single line, but that doesn't resolve the issue. I've also tried a bunch of variations: different versions, added _2.10 to the end of the artifactId, etc.
According to the docs (spark-submit --help):
The format for the coordinates should be groupId:artifactId:version.
So what I have should be valid and should reference this package.
If it helps, I'm running Cloudera 5.4.4.
What am I doing wrong? How can I reference the hbase packages correctly?
A list of packages should be separated using commas without whitespaces (breaking lines should work just fine) for example
--packages org.apache.spark:spark-streaming-kafka_2.10:1.3.0,\
org.apache.hbase:hbase-common:1.0.0
I found it worthy to use SparkSession in spark version 3.0.0 for mysql and postgres
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('mysql-postgres').config('spark.jars.packages', 'mysql:mysql-connector-java:8.0.20,org.postgresql:postgresql:42.2.16').getOrCreate()
#Mohammad thanks for this input. This worked for me too. I had to load the Kafka and msql packages in a single sparksession. I did something like this:
spark = (SparkSession .builder ... .appName('myapp') # Add kafka and msql package .config("spark.jars.packages", "org.apache.spark:spark-sql-kafka-0-10_2.12:3.1.2,mysql:mysql-connector-java:8.0.26") .getOrCreate())