PySpark SQL Recipes : with HiveQL, Dataframe and Graphframes /: with HiveQL, Dataframe and Graphframes. (2019)

• Record Type: Book
• Further Information: Note: Raju Kumar Mishra and Sundar Rajan Raman.
• Authors: Mishra, Raju Kumar
• Other Names: Raman, Sundar Rajan
• Contents: Chapter 1: Introduction to PySparkSQL Chapter Goal: Reader will understand about PySpark, PySparkSQL, Catalyst Optimizer, Project Tungsten and Hive No of pages 20-30 Sub -Topics 1. PySpark 2. PySparkSQL 3. Hive 4. Catalyst 5. Project Tungsten Chapter 2: Some time with Installation Chapter Goal: Learner will understand about installation of Spark, Hive, PostgreSQL, MySQL, MongoDB, Cassandra etc. No of pages: 30 -40 Sub - Topics 1. Installation Spark 2. Installation Hive 3. Installation MySQL 4. Installation MongoDB Chapter 3: IO in PySparkSQL Chapter Goal: This chapter will provide recipes to the reader, which will enable them to create PySparkSQL DataFrame from different sources. No of pages : 40-50 Sub - Topics: 1. Creating DataFrame from data. 2. Reading csv file to create Dataframe 3. Reading JSON file to create Dataframe. 4. Saving DataFrames to different formats. Chapter 4 : Operations on PySparkSQL DataFrames Chapter Goal: Reader will learn about data filtering, data manuipulation, data descriptive analysis, Dealing with missing value etc No Of Pages ; 40 -50 1. Data filtering 2. Data manipulation 3. Row and column manipulation Chapter 5 : Data Merging and Data Aggregation using PySparkSQL Chapter Goal: Reader will learn about data merging and aggregation using PySparkSQL 1. Data Merging 2. Data aggregation Chapter 6: SQL, NoSQL and PySparkSQL Chapter Goal: Reader will learn to run SQL and HiveQL queries on Dataframe No of pages: 30-40 Sub - Topics: 1. Running SQL on DataFrame 2. Running HiveQL Chapter 7: Structured Streaming Chapter Goal: Reader will understand about structured streaming No of pages : 30-40 1. Different type of modes. 2. Data aggregation in structured streaming 3. Different type of sources Chapter 8 : Optimizing PySparkSQL Chapter Goal: Reader will learn about optimizing PySparkSQL No Of pages : 20-30 Optimizing PySparkSQL Chapter 9 : GraphFrames Chapter Goal: Reader will understand about graph data analysis with Graphframes. No of pages : 30-40 1. GraphFrame Creation 1. Page Rank 2. Breadth First Search.
• Publisher Details: Place of publication not identified : Springer Nature Apress
• Publication Date: 2019
• Extent: 1 online resource
• Subjects: 005.13/3; COMPUTERS / General; Python (Computer program language); SPARK (Computer program language); Big data; Electronic books
• Languages: English
• ISBNs: 9781484243350; 1484243358
• Related ISBNs: 9781484243343
• Notes: Note: Online resource; title from PDF title page (EBSCO, viewed March 26, 2019).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.