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big-data's Introduction

Big Data

Lambda Architecture

  • Batch layer

    • Master dataset
    • batch view = funciton (all data)
    • Technology: Hadoop
  • Speed layer

    • Realtime views
    • realtime view = funciton (realtime view, new data)
  • Serving layer

    • Batch views
    • query = funciton (batch view, realtime view)
    • Technology: ElephantDB
  • *Technologies

    • Batch computatinon systems: Hadoop MapReduce, Hadoop Distributed File System (HDFS)
    • Serialization frameworks: Trhift, Protocol Buffers, Avro
    • Random-access NoSQL databases: Cassandra, HBase, MongoDB, Voltemort, Riak, CouchDB
    • Messaging/queuing systems: Kafka
    • Realtime computation systems: Storm

Data model for Big Data

  • Fact-based model
    • Data is raw
    • Data is immutable
    • Data is eternally true
  • Thrift
    • https://thrift.apache.org/
    • https://thrift.apache.org/tutorial/java
    • https://media.readthedocs.org/pdf/thrift-tutorial/latest/thrift-tutorial.pdf
    • Thrift structs are the equivalent of classes in OOP languages but without inheritance. A struct has a set of strongly typed fields, each with a unique name as an identifier. Fields may have various annotations (numeric field IDs, optional default values, etc.).
    • Two different ways to generate the Java source code from the thrift file (see examples under thrift-example-1 and thrift-example-2):
      • Option 1: Run mvn clean generate-sources having configured the libthrift library in the pom.xml. It will be generated under target/generated-sources
      • Option 2: Manually generate the sources with the thrift command from a terminal, indicating the destination folder

Batch layer

Speed layer

TBD

Serving layer

TBD

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