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Bleu Framework for Hbase & Hadoop

Bleu Framework for Hbase & Hadoop

Presentation for Cloud-based applications

Bleu (Jia-Huei Ren)

January 06, 2015
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  1. Behavior • Increase the machine will automatically expand the data

    storage. • The schema-less format of a Key-Value. • CAP – Consistent – Availability – Partition Tolerance
  2. Availability • A guarantee that every request receives a response

    about whether it was successful or failed.
  3. Partition Tolerance • The system continues to operate despite arbitrary

    message loss or failure of part of the system.
  4. Thrift Struct Exception Function struct TCell struct ColumnDescriptor struct TRegionInfo

    struct Mutation struct BatchMutation struct TIncrement struct TColumn struct TRowResult struct TScan exception IOError exception IllegalArgument exception AlreadyExists enableTable() disableTable() bool isTableEnabled() getTableNames() getColumnDescriptors() createTable() deleteTable() get() getRow() getRowWithColumns() getRows() mutateRow() mutateRows() deleteAll() deleteAllRow() scannerOpen() scannerGet() scannerClose()
  5. Performance Comparison 0 50 100 150 200 250 300 350

    400 450 500 1000 20000 100000 1000000 2000000 Hadoop MySQL
  6. Conclusions • Use Thrift-PHP will reduce the performance of Hbase.

    • This framework can easily switch between NoSQL database and RDBMS. • ORM design gives this framework more readable.