A = Np.zeros(shape(2,3)) Code Example
Example 1: declare numpy zeros matrix python
import numpy as np dimensions = (3, 3) np.zeros(dimensions) # 3x3 zeros matrixExample 2: np.zeros([8,8,3])
>>> np.zeros([8,8,3]) array([[ 0.], [ 0.]])Are Regular VACUUM ANALYZE Still Recommended Under 9.1?
Answer : VACUUM is only needed on updated or deleted rows in non-temporary tables. Obviously you're doing lots of INSERTs but it's not obvious from the description that you're also doing lots of UPDATEs or DELETEs. These operations can be tracked with the pg_stat_all_tables view, specifically the n_tup_upd and n_tup_del columns. Also, even more to the point, there is a n_dead_tup column that tells, per table, how much rows need to be vacuumed. (see Monitoring statistics in the doc for functions and views related to statistics gathering). A possible strategy in your case would be to suppress the scheduled VACUUM, keeping an eye on this view and checking on which tables the n_dead_tup is going up significantly. Then apply the aggressive VACUUM to these tables only. This will be a win if there are large tables whose rows never get deleted nor updated and the aggressive VACUUM is really necessary only on smaller tables. But keep running the ANALYZE for the optimiz
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