Revision 2050
Added by Aaron Marcuse-Kubitza about 12 years ago
| lib/sql.py | ||
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| 97 | 97 |
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| 98 | 98 |
class DbConn: |
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def __init__(self, db_config, serializable=True, log_debug=log_debug_none, |
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caching=False):
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caching=True):
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self.db_config = db_config |
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self.serializable = serializable |
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self.log_debug = log_debug |
| bin/map | ||
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| 96 | 96 |
in_table = opts.get_env_var('in_table', None, env_names)
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| 97 | 97 |
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# Optimization |
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cache_sql = opts.env_flag('cache_sql', False, env_names)
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cache_sql = opts.env_flag('cache_sql', True, env_names)
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by_col = in_db_config == out_db_config and opts.env_flag('by_col', False,
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env_names) # by-column optimization only applies if mapping to same DB |
| 102 | 102 |
if test: cpus_default = 0 |
Also available in: Unified diff
bin/map, sql.py: Turned SQL query caching back on because benchmarks of just the caching on vs. off reveal that it does reduce processing time significantly. However, there is a slowdown that was introduced between the time caching was added and the time the same XML tree was used for each node, which was giving the false indication that the slowdown was due to the caching.