Course Code

ApHadm1

Duration

21 hours (usually 3 days including breaks)

Requirements

Attendees are not required to have any specific skill as the training is focused on end users skills for both the administration and the manipulation of data under Apache Hadoop

Overview

이 과정은 개발자, 건축가, 데이터 과학자 또는 집중적으로 또는 정기적으로 데이터에 액세스해야하는 모든 프로필을 대상으로합니다.

이 과정의 주요 초점은 데이터 조작과 변형입니다.

Hadoop 생태계의 도구 Hadoop 과정에는 데이터 변환 및 조작에 많이 사용되는 Pig 및 Hive 사용이 포함됩니다.

이 교육은 또한 성능 메트릭 및 성능 최적화를 해결합니다.

이 과정은 전적으로 손에 있으며 이론적 인 측면의 프레젠테이션으로 강조 표시됩니다.

Machine Translated

Course Outline

1.1Hadoop Concepts

1.1.1HDFS

The Design of HDFS
Command line interface
Hadoop File System

1.1.2Clusters

Anatomy of a cluster
Mater Node / Slave node
Name Node / Data Node

1.2Data Manipulation

1.2.1MapReduce detailed

Map phase
Reduce phase
Shuffle

1.2.2Analytics with Map Reduce

Group-By with MapReduce
Frequency distributions and sorting with MapReduce
Plotting results (GNU Plot)
Histograms with MapReduce
Scatter plots with MapReduce
Parsing complex datasets
Counting with MapReduce and Combiners
Build reports

1.2.3Data Cleansing

Document Cleaning
Fuzzy string search
Record linkage / data deduplication
Transform and sort event dates
Validate source reliability
Trim Outliers

1.2.4Extracting and Transforming Data

Transforming logs
Using Apache Pig to filter
Using Apache Pig to sort
Using Apache Pig to sessionize

1.2.5Advanced Joins

Joining data in the Mapper using MapReduce
Joining data using Apache Pig replicated join
Joining sorted data using Apache Pig merge join
Joining skewed data using Apache Pig skewed join
Using a map-side join in Apache Hive
Using optimized full outer joins in Apache Hive
Joining data using an external key value store

1.3Performance Diagnosis and Optimization Techniques

Map
- Investigating spikes in input data
- Identifying map-side data skew problems
- Map task throughput
- Small files
- Unsplittable files
Reduce
- Too few or too many reducers
- Reduce-side data skew problems
- Reduce tasks throughput
- Slow shuffle and sort
Competing jobs and scheduler throttling
Stack dumps & unoptimized code
Hardware failures
CPU contention
Tasks
- Extracting and visualizing task execution times
- Profiling your map and reduce tasks
Avoid the reducer
Filter and project
Using the combiner
Fast sorting with comparators
Collecting skewed data
Reduce skew mitigation

회원 평가

★★★★★

교육에 대해 가장 좋아하는 점은 무엇입니까? : 각 도구에 대해 자세히 설명합니다.

Amber Mehrotra - NIIT Limited

Course:Hadoop Administration

Machine Translated

트레이너가 외부 디스크에 제공 한 이미 준비된 VM에서 모든 데이터와 소프트웨어를 사용할 준비가되었다는 사실.

vyzVoice

Course:Hadoop for Developers and Administrators

Machine Translated

트레이너가 예를 보여줍니다

Simon Hahn