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    Course Details

    Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple, extensible data model that allows for online analytic application.

    Apache Flume Training Overview

    Our Training deals with the basics of setting and executing commands. It has a simple and flexible architecture based on streaming data flows; and is robust and fault tolerant with tunable reliability mechanisms for failover and recovery. All these concepts are best explained in our curriculum.

    Apache Flume Training Curriculum

    Overview

    Architecture

    Data flow mode

    Reliability and Recoverability

    Configuring individual components

    Wiring the pieces together

    Data ingestion

    Network streams

    Consolidation

    Multiplexing the flow

    Configuration

    Defining the flow

    Configuring individual components

    Adding multiple flows in an agent

    Fan out flow

    Flume Sources

    Avro Source, Exec Source

    NetCat Source

    Sequence Generator Source

    Syslog Sources

    Syslog TCP Source

    Syslog UDP Source

    Legacy Sources

    Avro Legacy Source

    Thrift Legacy Source

    Custom Source

    HDFS Sink

    Logger Sink

    Avro Sink

    IRC Sink

    File Roll Sink

    Null Sink

    HbaseSinks

    HbaseSink

    AsyncHBaseSink

    Custom Sink

    Memory Channel

    JDBC Channel

    Recoverable Memory Channel

    File Channel, Pseudo Transaction Channel

    Custom Channel

    Flume Channel Selectors

    Replicating Channel Selector

    Multiplexing Channel Selector

    Custom Channel Selector

    Default Sink Processor

    Failover Sink Processor

    Load balancing Sink Processor

    Custom Sink Processor

    Timestamp Interceptor

    Host Interceptor

    Flume Properties

    Property

    Monitoring

    Troubleshooting

    Handling agent failures

    Compatibility

    HDFS

    AVRO

    Faqs

    Our trainers have relevant experience in implementing real-time solutions on different queries related to different topics. Mindmajix verifies their technical background and expertise.

    We record each LIVE class session you undergo through and we will share the recordings of each session/class.

    Trainer will provide the Environment/Server Access to the students and we ensure practical real-time experience and training by providing all the utilities required for the in-depth understanding of the course.

    If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within 48 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.

    The Training itself is Real-time Project Oriented.

    Yes. All the training sessions are LIVE Online Streaming using either through WebEx or GoToMeeting, thus promoting one-on-one trainer student Interaction.

    There are some Group discounts available if the participants are more than 2.

    As we are one of the leading providers of Online training, We have customers from USA, UK, Canada, Australia, UAE, Qatar, NZ, Singapore, Malaysia, India and other parts of the world. We are located in USA. Offering Online Training in Cities like

    Minneapolis, Melbourne, Jacksonville, Davidson, Murfreesboro, Auckland, Carlsbad,  San Marcos, Tacoma, Bellevue, Garland, Raleigh-Cary, Fort Lauderdale, Miami, Toronto, Wellington, Gilbert, Tempe, Alexandria, Chandler, Scottsdale, Peoria, Honolulu, Raleigh, Nashville, Plano, Montreal, Calgary, Edmonton, Saint John, Vancouver, Richmond, Mississauga, Saskatoon, Kingston, Kelowna, Hyderabad, Bangalore, Pune, Mumbai, Delhi, Dubai, Doha, Brisbane, Perth etc…

    • Apache Flume Training Washington, DC
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    • Apache Flume Training San Jose
    • Apache Flume Training St. Louis

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