Most engines feeds their query optimizers with different types of statistics, e.g histograms of most common values, fractions of NULL values, Number of Distinct Values, relation cardinality. The statistics allows to make educated guesses regarding cardinality of intermediate and final result of a query, e.g. optimizer finds the optimal join order using this statistics. MCS now has a rudimentary statistics that consist of a relation cardinality only.
We need to design and build facilities that allows MCS to make educated guesses about cardinality of intermediate and final result of a query and use this knowledge to produce an optimal plan.
What is statistics
The simplest version of statistics must have the list of attributes listed earlier. The improved version should have an extensible format to add attributes(e.g. correlated or dependant histograms on functionaly dependant columns) w/o lots of changes.
What triggers stats collection
There must be a user knob in the form of ANALYZE SQL statement. Bulk insert operation inserting more then N values must also trigger ANALYZE to regresh the stats.
ExeMgr or whatever the optimizer goes into is the most important consumer. The fact that there might be more then one EM in the cluster must be taken into account.
Where to put stats and how to save it b/w restarts
EMs in the cluster must have direct access to the stats so stats in-memory representation must reside in the RAM of the primary EM. Other EMs must have a synchronized version of the stats.
EM must initiate statistics collection. The statistics collection process must not differ much from SELECT * FROM query. The sampling method isn't yet choosen.
Please see the design doc for more details.