Spark - HiveWarehouseConnector Quick Setup

The purpose of this repo is to provide quick examples and utililities to work on a Spark and Hive integration on HDP 3.1.4

Prerequisites:

• HiveServer2Interactive (LLAP) installed, up and running.
• Bash and Python interpreter available.
• Ideally for connections using HTTP transport protocol, in the Ambari -> Hive -> Configs, hive.server2.thrift.http.cookie.auth.enabled should be 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 bellow 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:

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 inmediatly provide enough information with regard to:

1. The information to enable the Spark and Hive integration (HWConnector)
2. A working spark-shell command to test initial connectivity
3. A short how-to list all Databases in Hive, in scala.

LDAP/AD Authentication

Pre-requisite, refer to Spark - HWC, The initial setup process.

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’ll 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’ll 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.

Kerberos Authentication

For Kerberos authentication, pre-conditions have to be met:

1. Initial "kinit" has to always be executed and validated.

   $ kinit [email protected]
   Password for [email protected]:
   
   $ klist -v
   Credentials cache: API:501:9
       Principal: [email protected]
   Cache version: 0
   
   Server: krbtgt/[email protected]
   Client: [email protected]
   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
   

2. For YARN, HDFS, Hive and HBase long-running jobs DelegationTokens have to be fetched, so we'll have to provide "--keytab" and "--principal" extra arguments, i.e.:

   spark-submit $arg1 $arg2 $arg3 $arg-etc --keytab my_file.keytab 
   --principal [email protected] --class a.b.c.d app.jar
   

3. 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="[email protected]"; 
   };
   

   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/[[email protected]](mailto:[email protected])", "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=/tmp
livy.spark.datasource.hive.warehouse.metastoreUri=
livy.spark.hadoop.hive.llap.daemon.service.hosts=@llap0
livy.spark.jars=file:/
livy.spark.security.credentials.hiveserver2.enabled=true
livy.spark.sql.hive.hiveserver2.jdbc.url=jdbc:hive2://
livy.spark.sql.hive.hiveserver2.jdbc.url.principal=hive/_HOST@
livy.spark.submit.pyFiles=file:/
livy.spark.hadoop.hive.zookeeper.quorum=

Please note that compared to a regular spark-shellor 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.

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 we'll find a Python script to create and load a table based on an input table schema, written by Pablo Junge. The script file is available in this github repo as well HiveRandom.zip

Another short bash script is available show_create_cleaner.sh, and it can be used as:

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 tablestmt 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, specially 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 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.

Results 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