Spark 1.X Big Data Video tutorial

Course: Link: http://pan.baidu.com/s/1kTggcb9 Password: 9MFN

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Course Content:

First week spark eco-system overview and programming model

Spark Eco-System Overview

Review Hadoop MapReduce

Spark Run mode

RDD

Introduction to the Spark run-time model

Introduction to Caching policies

Transformation

Action

Lineage

Fault-tolerant processing

Wide dependence and narrow dependence

Cluster configuration

Next week dive into the spark kernel

Spark Terminology Explained

Cluster overview

Core components

Data locality

Common Rdd

Task scheduling

Dagscheduler

TaskScheduler

Task Details

Broadcast variables

Accumulator

Performance tuning

Third week spark on Yarn & Spark as a service

Spark on Yarn principle

Spark on Yarn Practice

JobServer architecture

JobServer API Introduction

JobServer Configuration and Deployment

The principle and practice of Spark streaming in the week four

DStream

Data source

Stateless transformation and stateful transformation

Checkpoint

Fault tolerant

Performance optimization

Week five shark with spark SQL

Shark Data Model

Shark data types

Shark architecture

Shark deployment

Cache (partition) table

Sharkserver

Shark combined with Spark

Spark SQL schema

Parquet Support

Dsl

SQL on RDD

Hive Support

Udf

JDBC Server

Six weeks machine learning on Spark

Linearregression

K-means

Collaborative Filtering

Seventh week spark multi-language programming

About Python

Pyspark API

Writing Spark programs using Python

Spark with Java

Eighth weekly calculation Graphx

The existing Diagram calculation framework

Table Operators

Graph Operators

GRAPHX Design

Nineth Week Tachyon principle and practice

Tachyon Principle and architecture

Tachyon Practice

Tenth Week Sparkr

Introduction to Sparkr Principle

Installation configuration and operation

Course Catalogue:

Viewing instructions (Must SEE)

Lesson 1, Training notes

Lesson 2, Spark eco-system overview and programming model

Lesson 3, Spark eco-system Overview and programming model (i)

Lesson 4, Spark eco-system Overview and programming model (II)

Lesson 5, Spark eco-system Overview and programming model (III)

Lesson 6, Spark eco-system Overview and programming model (IV)

Class 7, first week of work, please submit on September 21 before 12 o'clock in the evening

Lesson 8, Information

Lesson 9, Deep spark kernel (top)

Lesson 10, in-depth spark kernel (bottom)

11, second week of work, please submit before 12 o'clock in the evening on September 28

Lesson 12, Spark on yarn data

Lesson 13, JobServer information

Lesson 14, Spark on Yarn

Lesson 15, Spark as a Service

16, third week of work, please submit before 12 o'clock in the evening on October 5

Lesson 17, Streaming information

Lesson 18, Spark streaming (UP)

Lesson 19, Spark streaming (bottom)

Lesson 20, streaming-1.x (change)

21, fourth week of work, please submit before 12 o'clock in the evening on October 12

Lesson 22, Shark and Spark SQL data

Lesson 23, Shark (UP)

Lesson 24, Shark (next)

Lesson 25, Spark SQL (top)

Lesson 26, Spark SQL (bottom)

27, five weeks of work, please submit before 12 o'clock in the evening on October 19

Lesson 28, Sixth week course materials

Lesson 29, MLlib

Lesson 30, Spark 1.x change description

31, sixth week of work, please submit before 12 o'clock in the evening on October 26

Lesson 32, Seventh week information

Lesson 33, spark multi-language programming

Lesson 34, Supplemental instructions

35, seventh week of work, please submit before 12 o'clock in the evening on November 2

Lesson 36, Eighth week information

Lesson 37, Tachyon (1)

Lesson 38, Tachyon (2)

39, eighth week of work, please submit before 12 o'clock in the evening on November 9

Lesson 40, Nineth Week information

Lesson 41, Sparkr-part1

Lesson 42, Sparkr-part2

43, Nineth Week of work, please submit before 12 o'clock in the evening on November 16

Lesson 44, Tenth week information

Lesson 45, Graphx-part1

Lesson 46, Graphx-part2

Lesson 47, Graphx-part3

48, tenth week of work, please submit before 12 o'clock in the evening on November 23

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Spark 1.X Big Data Video tutorial