Cloudera Inc. is a United States-based software company that provides Apache Hadoop-based software, support and services, and training to business customers.
Cloudera's open-source Apache Hadoop distribution, CDH (Cloudera Distribution Including Apache Hadoop), targets enterprise-class deployments of that technology. Cloudera says that more than 50% of its engineering output is donated upstream to the various Apache-licensed open source projects (Apache Hive, Apache Avro, Apache HBase, and so on) that combine to form the Hadoop platform. Cloudera is also a sponsor of the Apache Software Foundation.
Big Data Cloudera 18:00 - 20:30 Tue, Thur, 07/11, 07/13, 07/18, 07/20
16:00 - 19:00 Sat 7/08, 7/15, 7/22
1、Cloudera Manager Installation- Introduction to Cloudera Manager Installation
- Cloudera Manager Requirements
- Cloudera Manager and Managed Service Databases
- Installing Cloudera Manager, CDH, and Managed Services
- Managing Software Distribution
- Understanding Custom Installation Solutions
- Deploying Clients
- Testing the Installation
- Uninstalling Cloudera Manager and Managed Software
- Troubleshooting Installation and Upgrade Problems
- Configuring Ports for Cloudera Manager
2、Apache Impala- Comments
- Data Types
- Literals
- SQL Operators
- Schema Objects and Object Names
- SQL Statements
- Built-In Functions
- SQL Differences Between Impala and Hive
- Porting SQL
3、Apache Hive- DDL Operations
- Creating Hive Tables
- Browsing through Tables
- Altering and Dropping Tables
- Metadata Store
- SQL Operations
- SELECTS and FILTERS
- GROUP BY
- JOIN
- MULTITABLE INSERT
- STREAMING
- DML Operations
- Simple Example Use Cases
- MovieLens User Ratings
- Apache Weblog Data
4、Apache HBase - Conceptual View
- Physical View
- Namespace
- Table
- Row
- Column Family
- Cells
- Data Model Operations
- Versions
- Sort Order
- Column Metadata
- Joins
- ACID
5、Hue- Import Data into HDFS
- Create Table from File
- Analyze Data with Query Editor
- Visualize and Download Results
6、Spark - Running Your First Spark Application
- Spark Application Overview
- Developing Spark Applications
- Running Spark Applications
- Spark and Hadoop Integration
- Data Analysis with Spark