Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)

Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)

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Starting from the basics, this course focuses on Spark 2.0, which is focused, concise and easy to understand, and is designed to be fast and flexible.
The course is based on practical exercises, providing a complete and detailed source code for learners to learn or apply to the project.

The course courseware is also very detailed, in the student is not convenient to watch the video when the direct reading courseware and the combination of source code, the same can achieve a good learning effect, and can greatly save study time.

The programming language in the course uses the current more promising scala,hadoop using the Cloudera 5.7.1 version of Hadoop, Kafka version 0.10.
In the course of the RDD operation, SQL, streaming development has a very in-depth systematic explanation, and around the enterprise requirements of the scene to expand and deepen.
The course does not involve the data mining algorithm package Mllib and graph calculation module parts which are less used in today's enterprises.

The Spark architecture architecture, application scenarios
New features at Spark 2.0 at a glance
03 Importing Spark-examples into IntelliJ idea
Cloudera Manager Installation
CDH5.7.1 cluster installation
CDH5.7.1 cluster Installation-cont.
Spark 2 cluster deployment and testing
Rdd to understand and create the RDD way
Transform of the operation of the RDD
Action operation and persistence of the RDD persist ()
One Pair Rdd operation
A detailed description of the common functions of the Pair RDD
13.Join and Cogroup
14 Add hive service and set MySQL metabase
15 [Project case] Website traffic UV and PV statistics
16 [Project case] session two hop rate statistics
The Spark SQL Basics Exercise
Sparksesion Grammar Exercises
19 [Project case] using Sparksesion for flow analysis
20 [Project Case]sparksesion Operation Hive
Package deployment in idea, validation of job results
Use of the Spark CLI command spark-sql
Spark-sql supports parameter-passing encapsulation
Spark-sql support for parametric encapsulation-cont.
UDF Development and application
+ Spark reads and writes JSON, parquet files
27 optimization-Control data partitioning and distribution
Spark Streaming architecture and concepts
Two types of Dstream, API introduction
Kafka Architecture system and concept
Kafka Cluster construction and testing
Streaming read Kafka Development WordCount case
33 using Updatestatebykey to perfect the case
34 Regional Sales by day
35 Time Window
36 de-weight class calculation case, with the calculation of UV as an example
37 [Stream Computing project] requirements description and architecture design
38 [Stream Computing Project]hbase DAO class development and testing
39 [Flow Calculation project]spark and servlet code explained
40 [Flow Calculation Project]highcharts code, project run

Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)