Advanced Hadoop for Developers Treningskurs

  1. Big Data Trening
  2. Hadoop Trening
  3. Advanced Hadoop for Developers Treningskurs

Kurskode

hadoopdeva

Varighet

21 timer (vanligvis 3 dag inkludert pauser)

Krav

  • comfortable with Java programming language (most programming exercises are in java)
  • comfortable in Linux environment (be able to navigate Linux command line, edit files using vi / nano)
  • a working  knowledge of Hadoop.

Lab environment

Zero Install: There is no need to install hadoop software on students’ machines! A working hadoop cluster will be provided for students.

Students will need the following

  • an SSH client (Linux and Mac already have ssh clients, for Windows Putty is recommended)
  • a browser to access the cluster. We recommend Firefox browser

Oversikt

Apache Hadoop er et av de mest populære rammene for behandling av Big Data på klynger av servere. Dette kurset går inn på datahåndtering i HDFS, advanced Pig, Hive og HBase. Disse avanserte programmeringsteknikkene vil være fordelaktige for erfarne Hadoop utviklere.

Publikum : utviklere

Varighet: tre dager

Format: forelesninger (50%) og praktiske laboratorier (50%).

Machine Translated

Kursplan

Section 1: Data Management in HDFS

  • Various Data Formats (JSON / Avro / Parquet)
  • Compression Schemes
  • Data Masking
  • Labs : Analyzing different data formats;  enabling compression

Section 2: Advanced Pig

  • User-defined Functions
  • Introduction to Pig Libraries (ElephantBird / Data-Fu)
  • Loading Complex Structured Data using Pig
  • Pig Tuning
  • Labs : advanced pig scripting, parsing complex data types

Section 3 : Advanced Hive

  • User-defined Functions
  • Compressed Tables
  • Hive Performance Tuning
  • Labs : creating compressed tables, evaluating table formats and configuration

Section 4 : Advanced HBase

  • Advanced Schema Modelling
  • Compression
  • Bulk Data Ingest
  • Wide-table / Tall-table comparison
  • HBase and Pig
  • HBase and Hive
  • HBase Performance Tuning
  • Labs : tuning HBase; accessing HBase data from Pig & Hive; Using Phoenix for data modeling

Testimonials

★★★★★
★★★★★

Related Categories

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