I understand that if MonetDB uses the timestamp as a filter (more selective), then it is faster. But does the MonetDB get this speed by purely sequence scan on timestamp column with 3,773,559,881 rows, or does it use some technique such as binary search?
Total row numbers are:
merge table: 3,773,559,881
current partition: 30,754,353
I get the the following performance numbers:
sql>select count(*) from mytable where timestamp between timestamp
'2016-04-15 13:05:05' and timestamp '2016-04-15 13:20:05' and abort_flag
in (0);
+--------+
| L1 |
+========+
| 735660 |
+--------+
1 tuple (1.0s)
----- 原始邮件 -----
发件人：Niels Nes
Hi,
I have a larger *merge table*, of which the relevant columns in this
query should be:
"timestamp" TIMESTAMP
"abort_flag" TINYINT
"timestamp" is roughly ascending, but far from monotonous.
"abort_flag" has a low cardinality with the following possible values
and number of occurrences:
| 0 | 735660 |
| 1 | 30119 |
| 2 | 1486 |
| 4 | 15 |
Both columns are completely populated.
Total row numbers are:
merge table: 3,773,559,881
current partition: 30,754,353
I get the the following performance numbers:
sql>select count(*) from mytable where timestamp between timestamp
'2016-04-15 13:05:05' and timestamp '2016-04-15 13:20:05' and abort_flag
in (0);
+--------+
| L1 |
+========+
| 735660 |
+--------+
1 tuple (1.0s)
sql>select count(*) from mytable where timestamp between timestamp
'2016-04-15 13:05:05' and timestamp '2016-04-15 13:20:05' and abort_flag
= 0;
+--------+
| L1 |
+========+
| 735660 |
+--------+
1 tuple (34.0s)
So there is a very significant, and IMHO surprising, performance
difference between the "equals" and the "in" comparison.
Well not that surprising. The choice on which operator in MonetDB isn't based on the content of the table but using relatively simpel rules. A equality is done before a range, and a range before an in. So in case of the in, the very selective range query is done first. In case of the equality, the equality is done first. Niels
Doing the same query directly against the sub table has a much more
consistent performance:
sql>select count(*) from mytable_20160415 where timestamp between
timestamp '2016-04-15 13:05:05' and timestamp '2016-04-15 13:20:05' and
abort_flag IN (0);
+--------+
| L1 |
+========+
| 735660 |
+--------+
1 tuple (618.914ms)
sql>select count(*) from mytable_20160415 where timestamp between
timestamp '2016-04-15 13:05:05' and timestamp '2016-04-15 13:20:05' and
abort_flag = 0;
+--------+
| L1 |
+========+
| 735660 |
+--------+
1 tuple (1.1s)
The same can be observed with another column, where ">= 4" is much
slower than the (in my case) equivalent "IN (4,5,6)".
I guess, for my uses I can always switch to the "in" conditions, because
all relevant columns should have very low cardinality, but in general,
this seems odd.
Is there an explanation for this behaviour, like optimizer problems with
merge tables? Or maybe a way to avoid it?
Regards,
Marc
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-- Niels Nes, Manager ITF, Centrum Wiskunde & Informatica (CWI) Science Park 123, 1098 XG Amsterdam, The Netherlands room L3.14, phone ++31 20 592-4098 sip:4098@sip.cwi.nl url: https://www.cwi.nl/people/niels e-mail: Niels.Nes@cwi.nl _______________________________________________ users-list mailing list users-list@monetdb.org https://www.monetdb.org/mailman/listinfo/users-list