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Sung-Soo Kim's Blog

Database Workloads

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22 January 2015


Database Workloads

  • Different tuning for different workloads
  • Different systems support different workloads
  • Trend towards mixed workloads
  • Trend towards real time (i.e, more on-line)

Big Data Anaytics

  • Complex analysis (on-line or batch) on
    • Large relational data warehouses + Web site access and search logs + Text corpora + Web data + Sensor data + … etc.
  • Supported by
    • Parallel database systems
    • MapReduce
  • Other systems also exist
    • SCOPE, Pregel, Spark, GraphLab, R, … etc.

Workload Management

  • Workloads include all queries/jobs and updates
  • Workloads can also include administrative utilities
  • Multiple users and applications
  • Different requirements
    • Development vs. production
    • Priorities

  • Manage the execution of multiple workloads to meet explicit or implicit service level objectives
  • Look beyond the performance of an individual request to the performance of an entire workload

Problems Addressed by Workload Management

  • Workload isolation
    • Important for multi-tenant systems
  • Priorities
    • How to interpret them?
  • Admission control and scheduling
  • Execution control
    • Kill, suspend, resume
  • Resource allocation
    • Including sharing and throttling
  • Monitoring and prediction
  • Query characterization and classification
  • Service level agreements

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