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.