Best Hadoop Training in Marathahalli
- Basics/Introduction : Multi-Threading , OpenMP (Open Multiprocessing) and MPI (Message Passing Interface), Performance tuning and optimization:-Matrix Multiplication, Uniqueword count problem, Distributed computing concepts, Designing and caveats, Distributed Debugging, Network challenges.
- Hadoop Overview : Why Hadoop?, Data Storage and Analysis, Hadoop v/s RDBMS, Brief history of Hadoop, Architecture of Hadoop, Overview of HDFS (Hadoop Distributed File System) and MR (Map Reduce) framework, Overview of problems solved by Hadoop, Data Mining, Web Mining, Natural Language Processing, K-means clustering, Sentimental Analysis.
- Setting up Hadoop: Pseudo Mode, Cluster, Common Errors when running Hadoop cluster, Incompatible name space IDs, Protocol version mismatch, Safe mode exception.
- HDFS- Hadoop Distributed File System: HDFS Design and Architecture, HDFS Concepts, Interacting HDFS using command line, Interacting HDFS using JAVA APIs, Running MR application on Local File system, pseudo mode, cluster mode, Creating and deleting directories on HDFS, Creating and deleting files on HDFS, Reading and writing files on HDFS, Moving files with in HDFS, Renaming files, Submitting Jobs, Data flow while reading and writing.
- Map Reduce Programming Model : Developing Map Reduce Application, Configuring environment, Writing Junit test cases for Mapper, Reducer and Driver, Using local runner, Running on pseudo mode, Running on cluster mode, Launching the job, Using Command Line, Using Java API, Tuning the job, Using Combiner, Using Compression, Using HProf (Profiler), Phases in Map Reduce Framework, Partitioning, Shuffling and Sorting, How Hadoop runs a Map Reduce Job, Job Submission, Job Initialization, Task Assignment, Task Execution, Map Reduce Input and Output Formats, Text IO, Sequence IO, KeyValue IO, DataBase IO, Advance Concepts, Chain Mapper and Chain Reducer, Using Counters, Distributed Cache
- Hadoop Programming Languages : Hive, Installation, Creating tables, Writing Hive Queries, Pig, Installation, Concepts, Data processing operators, Writing UDFs.
- No SQL Data Bases –Mongodb: Concepts- SQL v/s NoSQL
- Case Studies / Projects
- HDFS Monitoring and Logging: Logging, Metrics, Audit Logging.
- HDFS Maintenance: Commissioning and Decommissioning Node, Upgrading to new cluster.