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CHAPTER 6 LOCKING AND LATCHING
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In the first instance, our program will not use bind variables, but rather will use string concatenation to insert data (you will obviously have to use your own connect string for your system!): import java.sql.*; public class instest { static public void main(String args[]) throws Exception { DriverManager.registerDriver(new oracle.jdbc.driver.OracleDriver()); Connection conn = DriverManager.getConnection ("jdbc:oracle:thin:@localhost:1521:ora11gr2", "scott","tiger"); conn.setAutoCommit( false ); Statement stmt = conn.createStatement(); for( int i = 0; i < 25000; i++ ) { stmt.execute ("insert into "+ args[0] + " (x) values(" + i + ")" ); } conn.commit(); conn.close(); } } I ran the test in single user mode (that is, by itself with no other active database sessions), and the statspack report came back with this information: Elapsed: DB time: 0.65 (mins) Av Act Sess: 0.56 (mins) DB CPU: 0.9 0.56 (mins)
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Cache Sizes Begin End ~~~~~~~~~~~ ---------- ---------Buffer Cache: 100M Shared Pool: 144M Load Profile Per Second ~~~~~~~~~~~~ ----------------- Parses: 690.2 Hard parses: 652.4 Instance Efficiency Indicators ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Buffer Nowait %: 100.00 Buffer Hit %: 99.99 Library Hit %: 63.59 Execute to Parse %: 15.29 Parse CPU to Parse Elapsd %: 99.32
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Std Block Size: Log Buffer:
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Per Transaction Per Exec Per Call ----------------- ----------- ----------5,383.8 5,089.0
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Redo NoWait %: 100.00 Optimal W/A Exec %: 100.00 Soft Parse %: 5.48 Latch Hit %: 99.96 % Non-Parse CPU: 23.25
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Top 5 Timed Events Avg %Total ~~~~~~~~~~~~~~~~~~ wait Call Event Waits Time (s) (ms) Time ----------------------------------------- ------------ ----------- ------ -----CPU time 32 97.4 log file parallel write 72 0 5 1.1 control file parallel write 17 0 11 .6 db file async I/O submit 11 0 13 .4 os thread startup 2 0 50 .3 I included the SGA configuration for reference, but the relevant statistics are as follows: Elapsed (DB time) time of approximately 39 seconds (0.65 of a minute) 652 hard parses per second 32 CPU seconds used
Now, if we were to run two of these programs simultaneously, we might expect the hard parsing to jump to about 1,200/1,300 per second (we have two CPUs available, after all) and the CPU time to double to perhaps 64 CPU seconds. Let s take a look: Elapsed: DB time: 1.08 (mins) Av Act Sess: 1.98 (mins) DB CPU: 1.8 1.96 (mins)
Load Profile Per Second ~~~~~~~~~~~~ -----------------... Parses: 826.6 Hard parses: 780.1 ... Instance Efficiency Indicators ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Buffer Nowait %: 100.00 Buffer Hit %: 99.99 Library Hit %: 63.55 Execute to Parse %: 13.81 Parse CPU to Parse Elapsd %: 96.44
Per Transaction Per Exec Per Call ----------------- ----------- ----------2,238.6 2,112.7
Redo NoWait %: 100.00 Optimal W/A Exec %: 100.00 Soft Parse %: 5.62 Latch Hit %: 96.80 % Non-Parse CPU: 25.51
Top 5 Timed Events Avg %Total ~~~~~~~~~~~~~~~~~~ wait Call Event Waits Time (s) (ms) Time ----------------------------------------- ------------ ----------- ------ -----CPU time 103 96.1 latch: shared pool 15,814 2 0 1.9 log file parallel write 112 1 8 .8 db file async I/O submit 11 0 35 .4 control file parallel write 34 0 11 .4 What we discover is that the hard parsing goes up a little bit, but the CPU time triples rather than doubles! How could that be The answer lies in Oracle s implementation of latching. On this multi-CPU machine, when we could not immediately get a latch, we spun. The act of spinning itself consumes CPU. Process 1 attempted many times to get a latch onto the shared pool only to discover that process 2 held
CHAPTER 6 LOCKING AND LATCHING
that latch, so process 1 had to spin and wait for it (consuming CPU). The converse would be true for process 2; many times it would find that process 1 was holding the latch to the resource it needed. So, much of our processing time was spent not doing real work, but waiting for a resource to become available. If we page down through the statspack report to the Latch Sleep Breakdown report, we discover the following: Get Spin Latch Name Requests Misses Sleeps Gets -------------------------- --------------- ------------ ----------- ----------shared pool 2,311,383 133,507 16,143 117,695 row cache objects 985,847 28,722 4 28,719 Note how the number 16,143 appears in the SLEEPS column here That number corresponds very closely to the number of waits reported in the preceding Top 5 Timed Events report.
Note The number of sleeps corresponds closely to the number of waits; this might raise an eyebrow. Why not
exactly The reason is that the act of taking a snapshot is not atomic; a series of queries are executed gathering statistics into tables during a statspack snapshot, and each query is as of a slightly different point in time. So, the wait event metrics were gathered at a time slightly before the latching details were.
Our Latch Sleep Breakdown report shows us the number of times we tried to get a latch and failed in the spin loop. That means the Top 5 report is showing us only the tip of the iceberg with regard to latching issues the 133,507 misses (which means we spun trying to get the latch) are not revealed in the Top 5 report for us. After examination of the Top 5 report, we might not be inclined to think we have a hard parse problem here, even though we have a very serious one. To perform 2 units of work, we needed to use 3 units of CPU. This was due entirely to the fact that we need that shared resource, the shared pool. Such is the nature of latching. You can see that it can be very hard to diagnose a latching-related issue, unless you understand the mechanics of how they are implemented. A quick glance at a statspack report, using the Top 5 section, might cause us to miss the fact that we have a fairly bad scaling issue on our hands. Only by deeper investigation in the latching section of the statspack report will we see the problem at hand. Additionally, it is not normally possible to determine how much of the CPU time used by the system is due to this spinning all we know in looking at the two-user test is that we used 102 seconds of CPU time and that we missed getting a latch on the shared pool 133,507 times. We don t know how many times we spun trying to get the latch each time we missed, so we have no real way of gauging how much of the CPU time was spent spinning and how much was spent processing. We need multiple data points to derive that information. In our tests, because we have the single-user example for comparison, we can conclude that about 39 CPU seconds or so was spent spinning on the latch, waiting for that resource. We can come to this conclusion because we know that a single user needs only 32 seconds of CPU time so two single users would need 64 seconds, and 103 (total CPU seconds)minus 64 is 39.
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