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P. Burte, B. Aleman-Meza, D. Brent Weatherly, Rong Wu
                    University of Georgia
                       May 06, 2006
Repsented by :Mohamed Zeinelabdeen
•   In traditional database systems rely on the
    disk subsystem to retrieve and update data
    and use an offline storage device such as
    magnetic tape for backup.
•   In this experiment, a main-memory database
    will use physical memory as primary storage
    and a disk subsystem for backup.
•   A Java object, class Transaction, encapsulates
    all operations that are accessible by a
    database transaction.
•   The data set used for testing had 80 different
    extents. A total of 1,000 Transactions were
    run via 1,000 threads (one transaction per
    thread).
•   Each Transaction executed a fixed number of
    operations on each set of tests , each
    operation involves a single extent, which is
    chosen randomly from the 80 possibilities.
•   Each set of tests was run with different
    percentages of updates/queries.
   The different percentages tested were:
    ◦   0% updates, 100% queries .
    ◦   20% updates, 80% queries.
    ◦   40% updates, 60% queries.
    ◦   60% updates, 40% queries.
    ◦   80% updates, 20% queries.
    ◦   98% updates, 2% queries .
   For each of these tests, the following information was
    recorded:
    ◦ time taken for completion of all the transactions.
    ◦ average number of times a transaction needed to wait for
      an extent used by other transaction.
    ◦ number of transactions aborted because of a detected
      Deadlock .
   Each of the tests was run several times to in order to
    obtain an average for each value.
   Transaction performance is measured in
    two areas:
   the throughput for transaction
    completion.
   the average number of times a
    transaction goes to 'wait' state because it
    is unable to obtain a lock on a resource.
   Transaction throughput is measured by
    taking the total number of transactions
    attempted, subtracting the number of
    transactions that were aborted because of
    deadlock, and dividing by the time required
    to complete the test.
Transaction management for a main memory database
•   For the set of tests executing only one
    operation per transaction, the number of
    wait-states increased slowly for percentages
    of updates under 60%.
•   For percentages of updates over 60%, the
    number of wait-states increased rapidly.
•   For the set of tests executing 1 to 5
    operations per transaction, the number of
    wait-states increased with the percentage of
    updates increasing.
Transaction management for a main memory database
   for deadlock detection, the test results were
    as expected. The number of aborted
    transactions because of a detected deadlock
    increases as the percentage of updates
    increases.
   no deadlock occurs if all transactions contain
    a single operation on a single extent.
Transaction management for a main memory database
   From this experiment, Inferred performance
    tests show our implementation is promising
    an average throughput of two hundred and
    thirty transactions per second for a thousand
    single-operation transactions is a good start.

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Transaction management for a main memory database

  • 1. P. Burte, B. Aleman-Meza, D. Brent Weatherly, Rong Wu University of Georgia May 06, 2006 Repsented by :Mohamed Zeinelabdeen
  • 2. In traditional database systems rely on the disk subsystem to retrieve and update data and use an offline storage device such as magnetic tape for backup. • In this experiment, a main-memory database will use physical memory as primary storage and a disk subsystem for backup. • A Java object, class Transaction, encapsulates all operations that are accessible by a database transaction.
  • 3. The data set used for testing had 80 different extents. A total of 1,000 Transactions were run via 1,000 threads (one transaction per thread). • Each Transaction executed a fixed number of operations on each set of tests , each operation involves a single extent, which is chosen randomly from the 80 possibilities. • Each set of tests was run with different percentages of updates/queries.
  • 4. The different percentages tested were: ◦ 0% updates, 100% queries . ◦ 20% updates, 80% queries. ◦ 40% updates, 60% queries. ◦ 60% updates, 40% queries. ◦ 80% updates, 20% queries. ◦ 98% updates, 2% queries .  For each of these tests, the following information was recorded: ◦ time taken for completion of all the transactions. ◦ average number of times a transaction needed to wait for an extent used by other transaction. ◦ number of transactions aborted because of a detected Deadlock .  Each of the tests was run several times to in order to obtain an average for each value.
  • 5. Transaction performance is measured in two areas:  the throughput for transaction completion.  the average number of times a transaction goes to 'wait' state because it is unable to obtain a lock on a resource.
  • 6. Transaction throughput is measured by taking the total number of transactions attempted, subtracting the number of transactions that were aborted because of deadlock, and dividing by the time required to complete the test.
  • 8. For the set of tests executing only one operation per transaction, the number of wait-states increased slowly for percentages of updates under 60%. • For percentages of updates over 60%, the number of wait-states increased rapidly. • For the set of tests executing 1 to 5 operations per transaction, the number of wait-states increased with the percentage of updates increasing.
  • 10. for deadlock detection, the test results were as expected. The number of aborted transactions because of a detected deadlock increases as the percentage of updates increases.  no deadlock occurs if all transactions contain a single operation on a single extent.
  • 12. From this experiment, Inferred performance tests show our implementation is promising an average throughput of two hundred and thirty transactions per second for a thousand single-operation transactions is a good start.