Merge pull request #45 from NextThought/cache-docs

Update zeo-client-cache-tracing to use accurate script names.

doc/zeo-client-cache-tracing.txt

@@ -34,11 +34,12 @@ name or IP address) are logged.
 Analyzing a Cache Trace
 -----------------------
 
-The stats.py command-line tool is the first-line tool to analyze a cache
-trace.  Its default output consists of two parts:  a one-line summary of
-essential statistics for each segment of 15 minutes, interspersed with lines
-indicating client restarts, followed by a more detailed summary of overall
-statistics.
+The cache_stats.py command-line tool (``python -m
+ZEO.scripts.cache_stats``) is the first-line tool to analyze a cache
+trace. Its default output consists of two parts: a one-line summary of
+essential statistics for each segment of 15 minutes, interspersed with
+lines indicating client restarts, followed by a more detailed summary
+of overall statistics.
 
 The most important statistic is the "hit rate", a percentage indicating how
 many requests to load an object could be satisfied from the cache.  Hit rates
@@ -48,7 +49,7 @@ server's performance) by increasing the ZEO cache size.  This is normally
 configured using key ``cache_size`` in the ``zeoclient`` section of your
 configuration file.  The default cache size is 20 MB, which is small.
 
-The stats.py tool shows its command line syntax when invoked without
+The cache_stats.py tool shows its command line syntax when invoked without
 arguments.  The tracefile argument can be a gzipped file if it has a .gz
 extension.  It will be read from stdin (assuming uncompressed data) if the
 tracefile argument is '-'.
@@ -57,7 +58,7 @@ Simulating Different Cache Sizes
 --------------------------------
 
 Based on a cache trace file, you can make a prediction of how well the cache
-might do with a different cache size.  The simul.py tool runs a simulation of
+might do with a different cache size.  The cache_simul.py tool runs a simulation of
 the ZEO client cache implementation based upon the events read from a trace
 file.  A new simulation is started each time the trace file records a client
 restart event; if a trace file contains more than one restart event, a
@@ -66,7 +67,7 @@ statistics is added at the end.
 
 Example, assuming the trace file is in /tmp/cachetrace.log::
 
-    $ python simul.py -s 4 /tmp/cachetrace.log
+    $ python -m ZEO.scripts.cache_simul.py -s 4 /tmp/cachetrace.log
     CircularCacheSimulation, cache size 4,194,304 bytes
       START TIME  DURATION    LOADS     HITS INVALS WRITES HITRATE  EVICTS   INUSE
     Jul 22 22:22     39:09  3218856  1429329  24046  41517   44.4%   40776    99.8
@@ -80,7 +81,7 @@ by object eviction and not yet reused to hold another object's state).
 
 Let's try this again with an 8 MB cache::
 
-    $ python simul.py -s 8 /tmp/cachetrace.log
+    $ python -m ZEO.scripts.cache_simul.py -s 8 /tmp/cachetrace.log
     CircularCacheSimulation, cache size 8,388,608 bytes
       START TIME  DURATION    LOADS     HITS INVALS WRITES HITRATE  EVICTS   INUSE
     Jul 22 22:22     39:09  3218856  2182722  31315  41517   67.8%   40016   100.0
@@ -89,7 +90,7 @@ That's a huge improvement in hit rate, which isn't surprising since these are
 very small cache sizes.  The default cache size is 20 MB, which is still on
 the small side::
 
-    $ python simul.py /tmp/cachetrace.log
+    $ python -m ZEO.scripts.cache_simul.py /tmp/cachetrace.log
     CircularCacheSimulation, cache size 20,971,520 bytes
       START TIME  DURATION    LOADS     HITS INVALS WRITES HITRATE  EVICTS   INUSE
     Jul 22 22:22     39:09  3218856  2982589  37922  41517   92.7%   37761    99.9
@@ -97,7 +98,7 @@ the small side::
 Again a very nice improvement in hit rate, and there's not a lot of room left
 for improvement.  Let's try 100 MB::
 
-    $ python simul.py -s 100 /tmp/cachetrace.log
+    $ python -m ZEO.scripts.cache_simul.py -s 100 /tmp/cachetrace.log
     CircularCacheSimulation, cache size 104,857,600 bytes
       START TIME  DURATION    LOADS     HITS INVALS WRITES HITRATE  EVICTS   INUSE
     Jul 22 22:22     39:09  3218856  3218741  39572  41517  100.0%   22778   100.0
@@ -115,7 +116,7 @@ never loaded again.  If, for example, a third of the objects are loaded only
 once, it's quite possible for the theoretical maximum hit rate to be 67%, no
 matter how large the cache.
 
-The simul.py script also contains code to simulate different cache
+The cache_simul.py script also contains code to simulate different cache
 strategies.  Since none of these are implemented, and only the default cache
 strategy's code has been updated to be aware of MVCC, these are not further
 documented here.