The purpose of this repo is to provide quick examples and utilities to work on a Spark and Hive integration on HDP 3.1.4
Prerequisites:
HiveServer2Interactive (LLAP) must be installed, up and running
Bash and Python interpreter must be available
Ideally, for connections using HTTP transport protocol, in the Ambari -> Hive -> Configs, hive.server2.thrift.http.cookie.auth.enabled should be set to true
Set hadoop.proxyuser.hive.hosts=* in the Ambari -> HDFS -> Configs -> Custom core-site section (core-site.xml, or mention at least the LLAP Hosts, HS2 Hosts and Spark client hosts separated by commas).
Once the LLAP service is up and running, the next step for this setup requires the following properties to be configured in the Spark client:
spark.datasource.hive.warehouse.load.staging.dir=
spark.datasource.hive.warehouse.metastoreUri=
spark.hadoop.hive.llap.daemon.service.hosts=
spark.jars=
spark.security.credentials.hiveserver2.enabled=
spark.sql.hive.hiveserver2.jdbc.url=
spark.sql.hive.hiveserver2.jdbc.url.principal=
spark.submit.pyFiles=
spark.hadoop.hive.zookeeper.quorum=
While the above information can be manually collected as explained in our Cloudera official documentation, the following steps will help in collecting the standard information and avoid making mistakes during the copy and paste process of parameter values between HS2I and Spark. Steps:
--Notice the connection is to the LLAP Host--
ssh root@my-llap-host
cd /tmp
wget https://raw.githubusercontent.com/dbompart/hive_warehouse_connector/master/hwc_info_collect.sh
chmod +x hwc_info_collect.sh
./hwc_info_collect.sh
The above script will immediately provide enough information with regard to the following:
The information to enable the Spark and Hive integration (HWConnector)
A working spark-shell command to test initial connectivity
A short how-to list all Databases in Hive, in scala.
Done !!!
LDAP/AD Authentication
In an LDAP enabled authentication setup, the username and password will be passed in plaintext. The recommendation is to Kerberize the cluster. Otherwise, expect to see the username and password exposed in clear text amongst the logs.
To provide username and password, we will have to specify them as part of the JDBC URL string in the following format:
jdbc:hive2://zk1:2181,zk2:2181,zk3:2181/;user=myusername;password=mypassword;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2-interactive
Note: We will need to URL encode the password if it has a special character. For example, user=hr1;password=BadPass#1 will translate to user=hr1;password=BadPass%231
This method is not fully supported for Spark HWC integration nor it is recommended.
Kerberos Authentication
For Kerberos authentication, the following pre-conditions have to be met:
Initial "kinit" has to always be executed and validated.
$ kinit dbompart@EXAMPLE.COM
Password for dbompart@EXAMPLE.COM:
$ klist -v
Credentials cache: API:501:9
Principal: dbompart@EXAMPLE.COM
Cache version: 0
Server: krbtgt/EXAMPLE.COM@EXAMPLE.COM
Client: dbompart@EXAMPLE.COM
Ticket etype: aes128-cts-hmac-sha1-96
Ticket length: 256
Auth time: Feb 11 16:11:36 2013
End time: Feb 12 02:11:22 2013
Renew till: Feb 18 16:11:36 2013
Ticket flags: pre-authent, initial, renewable, forwardable
Addresses: addressless
For YARN, HDFS, Hive and HBase long-running jobs, DelegationTokens have to be fetched. Hence, provide "--keytab" and "--principal" extra arguments, i.e.:
spark-submit $arg1 $arg2 $arg3 $arg-etc --keytab my_file.keytab
--principal dbompart@EXAMPLE.COM --class a.b.c.d app.jar
For Kafka, a JAAS file has to be provided:
With a keytab, recommended for long running jobs:
KafkaClient {
com.sun.security.auth.module.Krb5LoginModule required
useKeyTab=true
keyTab="./my_file.keytab"
storeKey=true
useTicketCache=false
serviceName="kafka"
principal="user@EXAMPLE.COM";
};
Without a keytab, usually used for batch jobs:
KafkaClient {
com.sun.security.auth.module.Krb5LoginModule required
useTicketCache=true
renewTicket=true
serviceName="kafka";
};
And, it also has to be mentioned at the JVM level:
spark-submit $arg1 $arg2 $arg3 $arg-etc --files jaas.conf
--conf spark.driver.extraJava.Options="-Djava.security.auth.login.config=./jaas.conf"
--conf spark.executor.extraJavaOptions=-Djava.security.auth.login.config=./jaas.conf"
Livy2 - Example
curl -X POST --data '{"kind": "pyspark", "queue": "default", "conf": { "spark.jars": "/usr/hdp/current/hive_warehouse_connector/hive-warehouse-connector-assembly-1.0.0.3.1.4.32-1.jar", "spark.submit.pyFiles":"/usr/hdp/current/hive_warehouse_connector/pyspark_hwc-1.0.0.3.1.4.32-1.zip", "spark.hadoop.hive.llap.daemon.service.hosts": "@llap0","spark.sql.hive.hiveserver2.jdbc.url": "jdbc:hive2://[node2.cloudera.com:2181,node3.cloudera.com:2181,node4.cloudera.com:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2-interactive](http://node2.cloudera.com:2181,node3.cloudera.com:2181,node4.cloudera.com:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2-interactive)", "spark.yarn.security.credentials.hiveserver2.enabled": "false","spark.sql.hive.hiveserver2.jdbc.url.principal": "hive/[_HOST@EXAMPLE.COM](mailto:_HOST@EXAMPLE.COM)", "spark.datasource.hive.warehouse.load.staging.dir": "/tmp", "spark.datasource.hive.warehouse.metastoreUri": "thrift://node3.cloudera.com:9083", "spark.hadoop.hive.zookeeper.quorum": "[node2.cloudera.com:2181,node3.cloudera.com:2181,node4.cloudera.com:2181](http://node2.cloudera.com:2181,node3.cloudera.com:2181,node4.cloudera.com:2181)"}}' -H "X-Requested-By: admin" -H "Content-Type: application/json" --negotiate -u : [http://node3.cloudera.com:8999/sessions/](http://node3.cloudera.com:8999/sessions/) | python -mjson.tool
Submitting a brief example to show databases (hive.showDatabases()):
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/2/statements -X POST -H 'Content-Type: application/json' -H "X-Requested-By: admin" -d '{"code":"from pyspark_llap import HiveWarehouseSession"}'
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/2/statements -X POST -H 'Content-Type: application/json' -H "X-Requested-By: admin" -d '{"code":"hive = HiveWarehouseSession.session(spark).build()"}'
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/2/statements -X POST -H 'Content-Type: application/json' -H "X-Requested-By: admin" -d '{"code":"hive.showDatabases().show()"}'
Quick reference for basic API commands to check on the application status:
# Check sessions. Based on the ID field, update the following curl commands to replace "2" with $ID.
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/ | python -mjson.tool
# Check session status
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/2/status | python -mjson.tool
# Check session logs
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/2/log | python -mjson.tool
# Check session statements.
curl --negotiate -u : http://node2.cloudera.com:8999/sessions/2/statements | python -mjson.tool
Zeppelin - Example
Livy2 Interpreter
Assumptions:
The cluster is kerberized.
LLAP has already been enabled.
We got the initial setup information using the script hwc_info_collect.sh
In Ambari->Spark2->Configs->Advanced livy2-conf, the property livy.spark.deployMode should be set to either "yarn-cluster" or just plain "cluster". Note: Client mode is not supported.
Extra steps:
Add the following property=value in Ambari->Spark2->Configs->Custom livy2-conf section: - livy.file.local-dir-whitelist=/usr/hdp/current/hive_warehouse_connector/
We can test our configurations before setting them statically in the Interpreter:
Notebook > First paragraph:
%livy2.conf
livy.spark.datasource.hive.warehouse.load.staging.dir=$value
livy.spark.datasource.hive.warehouse.metastoreUri=$value
livy.spark.hadoop.hive.llap.daemon.service.hosts=$value
livy.spark.jars=file:///$value
livy.spark.security.credentials.hiveserver2.enabled=true
livy.spark.sql.hive.hiveserver2.jdbc.url=$value
livy.spark.sql.hive.hiveserver2.jdbc.url.principal=$value
livy.spark.submit.pyFiles=file:///$value
livy.spark.hadoop.hive.zookeeper.quorum=$value
Please note that compared to a regular spark-shell or spark-submit, this time we'll have to specify the filesystem scheme file:///, otherwise it'll try to reference a path on HDFS by default.
Notebook > Second paragraph:
%livy2
import com.hortonworks.hwc.HiveWarehouseSession
import com.hortonworks.hwc.HiveWarehouseSession._
val hive = HiveWarehouseSession.session(spark).build()
hive.showDatabases().show()
Creating a Table with Dummy data in Hive
For this specific task, we can expedite the table creation and dummy data ingest by referring to the Cloudera's VideoKB. In the above link, the Python script (HiveRandom.zip) should help you create and load a table based on an input table schema.
Another short bash script is available show_create_cleaner.sh, and it can be used as the following:
wget https://raw.githubusercontent.com/dbompart/hive_warehouse_connector/master/show_create_cleaner.sh
chmod +x show_create_cleaner.sh
./show_create_cleaner.sh show_create_table_output_file.txt
This bash script is a quick cleaner, it will make the Show create table stmt output re-usable in Hive or Spark by using --clean which will also remove the Table's Location and Table's Properties sections, i.e.:
./show_create_cleaner.sh show_create_table_output_file.txt --clean
Common errors
No service instances found in registry
Check again the configuration settings, especially the llap.daemon.service.hosts value and also the corresponding zNode which should be available and readable in from Zookeeper.
error: object hortonworks is not a member of package com
This usually means that either the HWC jar or zip files were not successfully uploaded to the Spark classpath. We can confirm this by looking at the logs and searching for:
Uploading resource file:/usr/hdp/current/hive_warehouse_connector/hive-warehouse-connector-assembly-1.0.0.3.1.4.32-1.jar
Cannot run get splits outside HS2
Add hive.fetch.task.conversion="more" To Custom hiveserver2-interactive section. And check the LLAP logs if needed.
Query returns no more than 1000
Follow the HWS API guide. This usually means that execute() method was incorrectly used instead of executeQuery().
"Blacklisted configuration values in session config: spark.master"
In the /etc/livy2/conf/spark-blacklist.conf file on the Livy2 server host, reconfigure this file to allow/disallow for configurations to be modified.
Unable to read HiveServer2 configs from ZooKeeper. Tried all existing HiveServer2 URIS from ZooKeeper
LLAP may not be up and running or there is a problem on reading its znode.
Suggested documentation
https://community.cloudera.com/t5/Community-Articles/Integrating-Apache-Hive-with-Apache-Spark-Hive-Warehouse/ta-p/249035
https://docs.cloudera.com/HDPDocuments/HDP3/HDP-3.1.4/integrating-hive/content/hive_hivewarehouseconnector_for_handling_apache_spark_data.html
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