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In the real world, you are of course free to choose your own toolbox when analyzing your log data. While there are many excellent open source frameworks and tools out there for log analytics-such as Elasticsearch-the intent of this two-part tutorial is to showcase how Spark can be leveraged for analyzing logs at scale. ![]() If you are interested in scalable SQL with Spark, feel free to check out SQL at scale with Spark. The intent of this case study-oriented tutorial is to take a hands-on approach showcasing how we can leverage Spark to perform log analytics at scale on semi-structured log data. Powered by big data, better and distributed computing, and frameworks like Apache Spark for big data processing and open source analytics, we can perform scalable log analytics on potentially billions of log messages daily. Gone are the days when we were limited to analyzing a data sample on a single machine due to compute constraints. Use klist command to check if Kerberos ticket is available. Now you are all set to connect to Hivesever2. #Spark url extractor driverConnect HiveServer 2 using Hive JDBC Driver for Apache Spark2 Get you local admins help if you are unable to fine keytab file and create keberos ticket. You can use knitcommand along with keytab file to create ticket. Steps to Connect HiveServer2 from Python using Hive JDBC Driversīefore connecting to Hive server, you must create Kerberos ticket. #Spark url extractor how toYou can read on how to set CLASSPATH variable in my another post Set and Use Environment Variable inside Python Script Note that, As jaydebeapi module is dependent on many other Hadoop specific jar files, it will not work if you don’t have all required jar files. If you are trying to execute form windows then you might want to set user specific environmental variables. export CLASSPATH=$CLASSPATH:$(hadoop classpath):/usr/hdp/current/hadoop-client/*:/usr/hdp/current/spark2-client/jars/*:/usr/hdp/current/hadoop-client/client/*Įxecute above command from your Linux edge node where kerberos ticket has been created. #Spark url extractor downloadYou can either download them or simply set Hadoop-client and Spark2-client path to CLASSPATH shell environmental variable. Hive Spark2 JDBC driver is dependent on many other Hadoop jars. #Spark url extractor installPip install Jaydebeapi3 Set CLASSPATH to Driver Location You can install it using pip: pip install Jaydebeapi It provides a Python DB-API v2.0 to that database. The JayDeBeApi module allows you to connect to any databases that supports JDBC driver. If you are using Python3, you should install Jaydebeapi3. Note that, example in this post uses Jaydebeapi for python 2. There are other options such as Pyspark that you can use to connect to HiveServer2. You can use the Hive Spark2 JDBC jar files along with Python Jaydebeapi open source module to connect to HiveServer2 remote server from your Python. ![]() JDBC driver jars comes with standard installation. Apache Spark comes with Hive JDBC driver for Spark2. Hive -Spark2 JDBC driver use thrift server, you should start thrift server before attempting to connect to remove HiveServer2. ![]() Hive JDBC driver is one of the most widely used driver to connect to HiveServer2.
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