The 1th chapter on Big Data
This chapter will explain why you need to learn big data, how to learn big data, how to quickly transform big data jobs, the contents of the actual combat course of this project, the pre-introduction of the practical course of the project, the introduction of development environment. We also introduce the knowledge of Hadoop and hive related to the project.
Chapter 2nd Overview of Spark and its biosphere
as the hottest big data processing technology in recent years, Spark is one of the skills necessary to become a big database engineer. This chapter gives a macro introduction to spark in the following ways: Spark's background, features, history, databricks official survey results, spark vs. Hadoop, spark development language, and run mode introduction ...
The 3rd Chapter of actual environment construction
工欲善其事 Its prerequisite, this chapter describes spark source compilation, spark local mode operation, Spark standalone mode run
Chapter 4th Spark SQL Overview
the advent of Spark SQL, which not only took over the baton of shark, continues to provide spark users with a high-performance SQL on Hadoop solution, but also brings a versatile, efficient, multi-dimensional, structured data processing capability to spark. This chapter will start with the spark SQL past life, SQL on Hadoop framework, Spark SQL Overview, Vision, architecture, and more ...
5th. Smooth transition from hive to spark SQL
Hive is the solution for Sql-on-hadoop and the default standard, and how to transition data processing from hive to spark SQL is what we have to master. In this chapter we will explain several ways to manipulate data in hive in Spark
6th Chapter Dateframe&dataset
Dataframe&dataset is the most central programming object in spark2.x, and the sub-framework in spark2.x can use DataFrame or datasets to interoperate with data. This chapter will explain the detailed programming development of DataFrame from the background of DataFrame, DataFrame contrast Rdd, DataFrame API operation, etc.
7th Chapter External Data Source
the core functionality of Spark SQL allows you to easily manipulate data in different formats stored on different systems using an external data source. This chapter explains how to use external data sources to manipulate data in hive, parquet, MySQL, and integrated use
8th Chapter Sparksql Vision
This chapter will explain the Spark's vision: Write less code, read less data, and let the optimizer automatically optimize the program
The 9th Chapter MU Lesson Net Diary actual combat
This chapter uses spark SQL to perform statistical analysis of each dimension of the access log for the master station, which involves data cleansing, data statistics, statistical results warehousing, data visualization, tuning, and Spark on YARN. Through this practical project will spark SQL in the knowledge points, to achieve the extrapolate effect ...
Chapter 10th Spark SQL extensions and summaries
This chapter summarizes the side-by-side aspects that spark SQL uses frequently in its work.
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Log analysis As an example enter big Data Spark SQL World total 10 chapters
