This course is designed for professionals from zero experience to already skilled professionals to enhance their Spark SQL Skills. Hands on session covers on end to end setup of Spark Cluster in AWS and in local systems.
COURSE UPDATED PERIODICALLY SINCE LAUNCH: Last Updated : December
What students are saying:
5 stars, This is classic. Spark related concepts are clearly explained with real life examples. – Temitayo Joseph
In data pipeline whether the data is in structured or in unstructured form, the final extracted data would be in structured form only. At the final stage we need to work with the structured data. SQL is popular query language to do analysis on structured data.
Apache spark facilitates distributed in–memory computing. Spark has inbuilt module called Spark–SQL for structured data processing. Users can mix SQL queries with Spark programs and seamlessly integrates with other constructs of Spark.
Spark SQL facilitates loading and writing data from various sources like RDBMS, NoSQL databases, Cloud storage like S3 and easily it can handle different format of data like Parquet, Avro, JSON and many more.
Spark Provides two types of APIs
Low Level API – RDD
High Level API – Dataframes and Datasets
Spark SQL amalgamates very well with various components of Spark like Spark Streaming, Spark Core and GraphX as it has good API integration between High level and low level APIs.
Courses : 3
Specification: Apache Spark SQL – Bigdata In-Memory Analytics Master Course
9 reviews for Apache Spark SQL – Bigdata In-Memory Analytics Master Course