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I need to know the number of rows in a table to calculate a percentage. If the total count is greater than some predefined constant, I will use the constant value. Otherwise, I will use the actual number of rows.
I can use SELECT count(*) FROM table. But if my constant value is 500,000 and I have 5,000,000,000 rows in my table, counting all rows will waste a lot of time.
Is it possible to stop counting as soon as my constant value is surpassed?
I need the exact number of rows only as long as it's below the given limit. Otherwise, if the count is above the limit, I use the limit value instead and want the answer as fast as possible.
Something like this:
SELECT text,count(*), percentual_calculus()
FROM token
GROUP BY text
ORDER BY count DESC;
Counting rows in big tables is known to be slow in PostgreSQL. The MVCC model requires a full count of live rows for a precise number. There are workarounds to speed this up dramatically if the count does not have to be exact like it seems to be in your case.
(Remember that even an "exact" count is potentially dead on arrival under concurrent write load.)
Exact count
Slow for big tables.
With concurrent write operations, it may be outdated the moment you get it.
SELECT count(*) AS exact_count FROM myschema.mytable;
Estimate
Extremely fast:
SELECT reltuples AS estimate FROM pg_class where relname = 'mytable';
Typically, the estimate is very close. How close, depends on whether ANALYZE or VACUUM are run enough - where "enough" is defined by the level of write activity to your table.
Safer estimate
The above ignores the possibility of multiple tables with the same name in one database - in different schemas. To account for that:
SELECT c.reltuples::bigint AS estimate
FROM pg_class c
JOIN pg_namespace n ON n.oid = c.relnamespace
WHERE c.relname = 'mytable'
AND n.nspname = 'myschema';
The cast to bigint formats the real number nicely, especially for big counts.
Better estimate
SELECT reltuples::bigint AS estimate
FROM pg_class
WHERE oid = 'myschema.mytable'::regclass;
Faster, simpler, safer, more elegant. See the manual on Object Identifier Types.
Replace 'myschema.mytable'::regclass with to_regclass('myschema.mytable') in Postgres 9.4+ to get nothing instead of an exception for invalid table names. See:
How to check if a table exists in a given schema
Better estimate yet (for very little added cost)
This does not work for partitioned tables because relpages is always -1 for the parent table (while reltuples contains an actual estimate covering all partitions) - tested in Postgres 14.
You have to add up estimates for all partitions instead.
We can do what the Postgres planner does. Quoting the Row Estimation Examples in the manual:
These numbers are current as of the last VACUUM or ANALYZE on the
table. The planner then fetches the actual current number of pages in
the table (this is a cheap operation, not requiring a table scan). If
that is different from relpages then reltuples is scaled
accordingly to arrive at a current number-of-rows estimate.
Postgres uses estimate_rel_size defined in src/backend/utils/adt/plancat.c, which also covers the corner case of no data in pg_class because the relation was never vacuumed. We can do something similar in SQL:
Minimal form
SELECT (reltuples / relpages * (pg_relation_size(oid) / 8192))::bigint
FROM pg_class
WHERE oid = 'mytable'::regclass; -- your table here
Safe and explicit
SELECT (CASE WHEN c.reltuples < 0 THEN NULL -- never vacuumed
WHEN c.relpages = 0 THEN float8 '0' -- empty table
ELSE c.reltuples / c.relpages END
* (pg_catalog.pg_relation_size(c.oid)
/ pg_catalog.current_setting('block_size')::int)
)::bigint
FROM pg_catalog.pg_class c
WHERE c.oid = 'myschema.mytable'::regclass; -- schema-qualified table here
Doesn't break with empty tables and tables that have never seen VACUUM or ANALYZE. The manual on pg_class:
If the table has never yet been vacuumed or analyzed, reltuples contains -1 indicating that the row count is unknown.
If this query returns NULL, run ANALYZE or VACUUM for the table and repeat. (Alternatively, you could estimate row width based on column types like Postgres does, but that's tedious and error-prone.)
If this query returns 0, the table seems to be empty. But I would ANALYZE to make sure. (And maybe check your autovacuum settings.)
Typically, block_size is 8192. current_setting('block_size')::int covers rare exceptions.
Table and schema qualifications make it immune to any search_path and scope.
Either way, the query consistently takes < 0.1 ms for me.
More Web resources:
The Postgres Wiki FAQ
The Postgres wiki pages for count estimates and count(*) performance
TABLESAMPLE SYSTEM (n) in Postgres 9.5+
SELECT 100 * count(*) AS estimate FROM mytable TABLESAMPLE SYSTEM (1);
Like #a_horse commented, the added clause for the SELECT command can be useful if statistics in pg_class are not current enough for some reason. For example:
No autovacuum running.
Immediately after a large INSERT / UPDATE / DELETE.
TEMPORARY tables (which are not covered by autovacuum).
This only looks at a random n % (1 in the example) selection of blocks and counts rows in it. A bigger sample increases the cost and reduces the error, your pick. Accuracy depends on more factors:
Distribution of row size. If a given block happens to hold wider than usual rows, the count is lower than usual etc.
Dead tuples or a FILLFACTOR occupy space per block. If unevenly distributed across the table, the estimate may be off.
General rounding errors.
Typically, the estimate from pg_class will be faster and more accurate.
Answer to actual question
First, I need to know the number of rows in that table, if the total
count is greater than some predefined constant,
And whether it ...
... is possible at the moment the count pass my constant value, it will
stop the counting (and not wait to finish the counting to inform the
row count is greater).
Yes. You can use a subquery with LIMIT:
SELECT count(*) FROM (SELECT 1 FROM token LIMIT 500000) t;
Postgres actually stops counting beyond the given limit, you get an exact and current count for up to n rows (500000 in the example), and n otherwise. Not nearly as fast as the estimate in pg_class, though.
I did this once in a postgres app by running:
EXPLAIN SELECT * FROM foo;
Then examining the output with a regex, or similar logic. For a simple SELECT *, the first line of output should look something like this:
Seq Scan on uids (cost=0.00..1.21 rows=8 width=75)
You can use the rows=(\d+) value as a rough estimate of the number of rows that would be returned, then only do the actual SELECT COUNT(*) if the estimate is, say, less than 1.5x your threshold (or whatever number you deem makes sense for your application).
Depending on the complexity of your query, this number may become less and less accurate. In fact, in my application, as we added joins and complex conditions, it became so inaccurate it was completely worthless, even to know how within a power of 100 how many rows we'd have returned, so we had to abandon that strategy.
But if your query is simple enough that Pg can predict within some reasonable margin of error how many rows it will return, it may work for you.
Reference taken from this Blog.
You can use below to query to find row count.
Using pg_class:
SELECT reltuples::bigint AS EstimatedCount
FROM pg_class
WHERE oid = 'public.TableName'::regclass;
Using pg_stat_user_tables:
SELECT
schemaname
,relname
,n_live_tup AS EstimatedCount
FROM pg_stat_user_tables
ORDER BY n_live_tup DESC;
How wide is the text column?
With a GROUP BY there's not much you can do to avoid a data scan (at least an index scan).
I'd recommend:
If possible, changing the schema to remove duplication of text data. This way the count will happen on a narrow foreign key field in the 'many' table.
Alternatively, creating a generated column with a HASH of the text, then GROUP BY the hash column.
Again, this is to decrease the workload (scan through a narrow column index)
Edit:
Your original question did not quite match your edit. I'm not sure if you're aware that the COUNT, when used with a GROUP BY, will return the count of items per group and not the count of items in the entire table.
You can also just SELECT MAX(id) FROM <table_name>; change id to whatever the PK of the table is
In Oracle, you could use rownum to limit the number of rows returned. I am guessing similar construct exists in other SQLs as well. So, for the example you gave, you could limit the number of rows returned to 500001 and apply a count(*) then:
SELECT (case when cnt > 500000 then 500000 else cnt end) myCnt
FROM (SELECT count(*) cnt FROM table WHERE rownum<=500001)
For SQL Server (2005 or above) a quick and reliable method is:
SELECT SUM (row_count)
FROM sys.dm_db_partition_stats
WHERE object_id=OBJECT_ID('MyTableName')
AND (index_id=0 or index_id=1);
Details about sys.dm_db_partition_stats are explained in MSDN
The query adds rows from all parts of a (possibly) partitioned table.
index_id=0 is an unordered table (Heap) and index_id=1 is an ordered table (clustered index)
Even faster (but unreliable) methods are detailed here.
I'm in the process of benchmarking some queries in redshift so that I can say something intelligent about changes I've made to a table, such as adding encodings and running a vacuum. I can query the stl_query table with a LIKE clause to find the queries I'm interested in, so I have the query id, but tables/views like stv_query_summary are much too granular and I'm not sure how to generate the summarization I need!
The gui dashboard shows the metrics I'm interested in, but the format is difficult to store for later analysis/comparison (in other words, I want to avoid taking screenshots). Is there a good way to rebuild that view with sql selects?
To add to Alex answer, I want to comment that stl_query table has the inconvenience that if the query was in a queue before the runtime then the queue time will be included in the run time and therefore the runtime won't be a very good indicator of performance for the query.
To understand the actual runtime of the query, check on stl_wlm_query for the total_exec_time.
select total_exec_time
from stl_wlm_query
where query='query_id'
There are some usefuls tools/scripts in https://github.com/awslabs/amazon-redshift-utils
Here is one of said scripts stripped out to give you query run times in milliseconds. Play with the filters, ordering etc to show the results you are looking for:
select userid, label, stl_query.query, trim(database) as database, trim(querytxt) as qrytext, starttime, endtime, datediff(milliseconds, starttime,endtime)::numeric(12,2) as run_milliseconds,
aborted, decode(alrt.event,'Very selective query filter','Filter','Scanned a large number of deleted rows','Deleted','Nested Loop Join in the query plan','Nested Loop','Distributed a large number of rows across the network','Distributed','Broadcasted a large number of rows across the network','Broadcast','Missing query planner statistics','Stats',alrt.event) as event
from stl_query
left outer join ( select query, trim(split_part(event,':',1)) as event from STL_ALERT_EVENT_LOG group by query, trim(split_part(event,':',1)) ) as alrt on alrt.query = stl_query.query
where userid <> 1
-- and (querytxt like 'SELECT%' or querytxt like 'select%' )
-- and database = ''
order by starttime desc
limit 100
I am running two sql queries say,
select obname from table1 where obid = 12
select modname from table2 where modid = 12
Both are taking very less time, say 300 ms each.
But when I am running:
select obname, modname
from (select obname from table1 where obid = 12) as alias1,
(select modname from table2 where modid = 12) as alias2
It is taking 3500ms. Why is it so?
In general, putting two scalar queries in the from clause is not going to affect performance. In fact, from an application perspective, one query may be faster because there is less overhead going back and forth to the database. A scalar query returns one column and one row.
However, if the queries are returning multiple rows, then your little comma is doing a massive Cartesian product (which is why I always use CROSS JOIN rather than a comma in a FROM clause). In that case, all bets are off, because the data has to be processed after the results start returning.
I've got a SQL Server 2005 database. I need to get distinct values in addition to calling a function on those distinct values. I'm not sure how the distinct works when there is a function call involved. For example, I have this query:
SELECT DISTINCT a, b, c, fcn_DoSomething(a, b, c) AS z FROM users
I'm guessing that the function (fcn_DoSomething) is being called for all of the values in the table, not the distinct values. Am I correct? If so, how can I write the query to call the function only on distinct values of a,b,c? I know one option is to use a temporary table, but if anyone has better ideas that would be great.
Thanks
This got me curious, so I did a bit of basic testing. I created a small table with some distinct and some repeating values, a function that just does string concatenation, and then looked at the execution plans for:
Go
DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE
select distinct cola, colb, dbo.sillyfunc(cola, colb)
from distincttest
--Clear the cache
Go
DBCC DROPCLEANBUFFERS
DBCC FREEPROCCACHE
select cola, colb, dbo.sillyfunc(cola, colb)
from (select distinct cola, colb from distincttest) as t
In this case, the execution plans showed clearly that the first one ran the concatenation function for every single row, but the second did the sort for distinct values first, then ran the function. But for a small number of rows, they had the same execution time, and when run together they showed each one using 50% of the total query resources.
So, I added a few hundred thousand repeating rows. and tried again. This changed the query plan so it was doing a hash match to get distinctness rather than the former sort, and now the second version which forced it to select for distinctness first executed more than ten times faster.
Finally, I thought there was a chance that this might just be because SQL Server had my sillyfunc marked as nondeterministic (select OBJECTPROPERTYEX(object_id('dbo.sillyfunc'), 'isdeterministic') returned 0), so I switched to patindex which was a builtin function and considered deterministic. This gave me the same results with the function being called for every row in the first version and just for the few distinct ones in the second version.
So, its possible that further testing would find situations that would coax the optimizer to do something more sophisticated, but it appears that if you want to apply the distinct before the function is called then you need to use something like a subquery, CTE, or temp table to limit what the function has access to.
This would ensure that the function only got called on distinct values.
select *, fcn_DoSomething(a, b, c)
from
(select distinct a,b,c FROM users) v
However, I believe that the function call will be optimised, so it may not make a difference. Give it a try.
SELECT DISTINCT tblJobReq.JobReqId
, tblJobReq.JobStatusId
, tblJobClass.JobClassId
, tblJobClass.Title
, tblJobReq.JobClassSubTitle
, tblJobAnnouncement.JobClassDesc
, tblJobAnnouncement.EndDate
, blJobAnnouncement.AgencyMktgVerbage
, tblJobAnnouncement.SpecInfo
, tblJobAnnouncement.Benefits
, tblSalary.MinRateSal
, tblSalary.MaxRateSal
, tblSalary.MinRateHour
, tblSalary.MaxRateHour
, tblJobClass.StatementEval
, tblJobReq.ApprovalDate
, tblJobReq.RecruiterId
, tblJobReq.AgencyId
FROM ((tblJobReq
LEFT JOIN tblJobAnnouncement ON tblJobReq.JobReqId = tblJobAnnouncement.JobReqId)
INNER JOIN tblJobClass ON tblJobReq.JobClassId = tblJobClass.JobClassId)
LEFT JOIN tblSalary ON tblJobClass.SalaryCode = tblSalary.SalaryCode
WHERE (tblJobReq.JobClassId in (SELECT JobClassId
from tblJobClass
WHERE tblJobClass.Title like '%Family Therapist%'))
When i try to execute the query it results in the following error.
Cannot sort a row of size 8130, which is greater than the allowable maximum of 8094
I checked and didn't find any solution. The only way is to truncate (substring())the "tblJobAnnouncement.JobClassDesc" in the query which has column size of around 8000.
Do we have any work around so that i need not truncate the values. Or Can this query be optimised? Any setting in SQL Server 2000?
The [non obvious] reason why SQL needs to SORT is the DISTINCT keyword.
Depending on the data and underlying table structures, you may be able to do away with this DISTINCT, and hence not trigger this error.
You readily found the alternative solution which is to truncate some of the fields in the SELECT list.
Edit: Answering "Can you please explain how DISTINCT would be the reason here?"
Generally, the fashion in which the DISTINCT requirement is satisfied varies with
the data context (expected number of rows, presence/absence of index, size of row...)
the version/make of the SQL implementation (the query optimizer in particular receives new or modified heuristics with each new version, sometimes resulting in alternate query plans for various constructs in various contexts)
Yet, all the possible plans associated with a "DISTINCT query" involve *some form* of sorting of the qualifying records. In its simplest form, the plan "fist" produces the list of qualifying rows (records) (the list of records which satisfy the WHERE/JOINs/etc. parts of the query) and then sorts this list (which possibly includes some duplicates), only retaining the very first occurrence of each distinct row. In other cases, for example when only a few columns are selected and when some index(es) covering these columns is(are) available, no explicit sorting step is used in the query plan but the reliance on an index implicitly implies the "sortability" of the underlying columns. In other cases yet, steps involving various forms of merging or hashing are selected by the query optimizer, and these too, eventually, imply the ability of comparing two rows.
Bottom line: DISTINCT implies some sorting.
In the specific case of the question, the error reported by SQL Server and preventing the completion of the query is that "Sorting is not possible on rows bigger than..." AND, the DISTINCT keyword is the only apparent reason for the query to require any sorting (BTW many other SQL constructs imply sorting: for example UNION) hence the idea of removing the DISTINCT (if it is logically possible).
In fact you should remove it, for test purposes, to assert that, without DISTINCT, the query completes OK (if only including some duplicates). Once this fact is confirmed, and if effectively the query could produce duplicate rows, look into ways of producing a duplicate-free query without the DISTINCT keyword; constructs involving subqueries can sometimes be used for this purpose.
An unrelated hint, is to use table aliases, using a short string to avoid repeating these long table names. For example (only did a few tables, but you get the idea...)
SELECT DISTINCT JR.JobReqId, JR.JobStatusId,
tblJobClass.JobClassId, tblJobClass.Title,
JR.JobClassSubTitle, JA.JobClassDesc, JA.EndDate, JA.AgencyMktgVerbage,
JA.SpecInfo, JA.Benefits,
S.MinRateSal, S.MaxRateSal, S.MinRateHour, S.MaxRateHour,
tblJobClass.StatementEval,
JR.ApprovalDate, JR.RecruiterId, JR.AgencyId
FROM (
(tblJobReq AS JR
LEFT JOIN tblJobAnnouncement AS JA ON JR.JobReqId = JA.JobReqId)
INNER JOIN tblJobClass ON tblJobReq.JobClassId = tblJobClass.JobClassId)
LEFT JOIN tblSalary AS S ON tblJobClass.SalaryCode = S.SalaryCode
WHERE (JR.JobClassId in
(SELECT JobClassId from tblJobClass
WHERE tblJobClass.Title like '%Family Therapist%'))
FYI, running this SQL command on your DB can fix the problem if it is caused by space that needs to be reclaimed after dropping variable length columns:
DBCC CLEANTABLE (0,[dbo.TableName])
See: http://msdn.microsoft.com/en-us/library/ms174418.aspx
This is a limitation of SQL Server 2000. You can:
Split it into two queries and combine elsewhere
SELECT ID, ColumnA, ColumnB FROM TableA JOIN TableB
SELECT ID, ColumnC, ColumnD FROM TableA JOIN TableB
Truncate the columns appropriately
SELECT LEFT(LongColumn,2000)...
Remove any redundant columns from the SELECT
SELECT ColumnA, ColumnB, --IDColumnNotUsedInOutput
FROM TableA
Migrate off of SQL Server 2000