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Data processing with Spark SQL

In this project, we will go through provisioning data for retrieval using Spark SQL.
4.54.5

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What will you learn

  • Spark SQL
  • Defining the dataframe schema
  • Saving final result in different formats
  • Setting up the spark SQL thrift server
  • Performance tuning
  • Benchmarking queries in Hive, Spark SQL, and impala

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • It is expected that students have a fair knowledge of Big Data and hadoop.

Project Description

Spark SQL offers the platform to provide a structured data to any dataset regardless its source or form. And once that structured data is formed, it can be queried using tools like Hive, Impala, and other Hadoop data warehouse tools.

In this project, we will go through some internal of Spark SQL to process the dataset, perform some joins with other supplementary data as well as make the data available for the query using the Spark SQL thrift server. On provision of the data, we will perform some interesting query and other go through some performance tuning technique for Spark SQL.

Instructors

 
Michael

Big Data & Enterprise Software Engineer

I am passionate about software development, databases, data analysis and the android platform. My native language is java but no one has stopped me so far from learning and using angular and node.js. Data and data analysis is thrilling and so are my experiences with SQL on Oracle, Microsoft SQL Server, Postgres and MyS see more...