SELECT /*+PARALLEL 8*/
A.ACC_ID,
COALESCE (B.PR_ID, NULL),
COALESCE (B.DESC, NULL),
COALESCE (B.CNT, 0)
FROM (SELECT ACC_ID
FROM ACC_ID_IN
WHERE XXX = 1 AND YYY = 'ABCD') A
LEFT OUTER JOIN
( SELECT /*+PARALLEL 8*/
A.ACC_ID,
B.PR_ID,
B.DESC,
COUNT (DISTINCT A.ACC_NBR) CNT
FROM DB1.TABLE1 A,
TABLE2 B,
TABLE3 C
WHERE A.ACC_ID IN (8888888888)
AND A.P_ID = B.P_ID
AND A.P_ID = C.P_ID
AND A.START <=TO_DATE (SUBSTR (A.ACC_ID, 1, 4) || '1231','YYYY/MM/DD')
AND A.END > TO_DATE (SUBSTR (A.ACC_ID, 1, 4) || '1230','YYYY/MM/DD')
GROUP BY A.ACC_ID, B.PR_ID, B.DESC
ORDER BY A.ACC_ID, B.PR_ID, B.DESC) B
ON A.ACC_ID = B.ACC_ID
WHERE A.ACC_ID IN (8888888888)
GROUP BY A.ACC_ID,
COALESCE (B.PR_ID, NULL),
COALESCE (B.DESC, NULL),
COALESCE (B.CNT, 0)
The above query with parallel hints taking very long time to execute where as same query executed in secs when I removed the parallel hints. This issue observed when oracle is upgraded to 19c. Could you please help me to understand what's happening here and do I need to perform any settings to enable parallel hints as part of DB upgrade activity.
Parallelism is tricky and there are many reasons why the degree of parallelism can be unexpected. Below are potential issues with your query, some of which others mentioned in comments:
Do you even want parallelism for such a fast query? Parallelism works harder, not smarter, so you generally only want to use it on large objects that take a long time to process. If the query runs in seconds without parallelism, it's probably not a good candidate for parallelism in the first place.
Statement level hints The /*+ PARALLEL */ hint at the top of the query applies to the whole statement, so you don't need to also add hints to other query blocks.
Incorrect hint format If you want to specify the degree of parallelism, you need to use parentheses around the number, like /*+ PARALLEL(8) */. Without the parentheses, Oracle will compute the degree of parallelism. I can't even remember all of the rules and details, but if you ask Oracle to generate the DOP for you, it will often times use CPU_COUNT * PARALLEL_THREADS_PER_CPU * NUMBER_OF_INSTANCES.
CPU_COUNT Since you've just upgraded, check if the CPU_COUNT was changed. On some platforms, such as Solaris, Oracle counts every virtual processor as a CPU, and then still multiplies it by PARALLEL_THREADS_PER_CPU, which can lead to ridiculous numbers. Although that parameter seems like something you wouldn't touch, I've shrunk the CPU_COUNT on many systems with good results. Run the below query to look at the most relevant parallel parameters.
select *
from v$parameter
where name in ('cpu_count', 'parallel_threads_per_cpu', 'parallel_degree_policy', 'parallel_degree_limit');
Find the Degree of Parallelism There are several ways to find the DOP and to find information on why the DOP was chosen. In 19c, the "Note" and "Hint Report" section of the explain plan can give detailed information on how the DOP was calculated. Use explain plan for select ... and then select * from table(dbms_xplan.display); to find that information. As astentx suggested, select dbms_sqltune.report_sql_monitor('&SQL_ID') from dual can also be a great help with long-running queries.
Instead of providing hint to the entire query - You can specify to a driving table.
/*+ parallel(A,8) */
and then produce a explain plan and see the DOP was in place or not.
Is optimizer_use_sql_plan_baselines and resource_manager_cpu_allocation oracle system parameter have impact on sql query performance.
We have two envt suppose A and B. On A Envt query is running fine but in Envt. B its tacking time. I have compared system parameter and found difference in values in optimizer_use_sql_plan_baselines and resource_manager_cpu_allocation .
SQL plan baselines and the resource manager certainly could have a huge impact on performance, and you should use the below two queries or confirm or deny that those parameters are related to your problem.
GV$SQL stores which SQL plan baseline is associated with each SQL statement. Compare the SQL_PLAN_BASELINE column in the below query, and if they are equal then your problem is not related to baselines:
select sql_plan_baseline, round(elapsed_time/1000000) elapsed_seconds, gv$sql.*
from gv$sql
order by elapsed_time desc;
The Active Session History (ASH) views can tell you if the resource manager is an issue. If your queries are being throttled then you will see an event
named "resmgr:cpu quantum" in the below query. (But pay attention to the counts - don't troubleshoot a wait event if it only happens a small number of times.)
select nvl(event, 'CPU') event, count(*)
from gv$active_session_history
group by event
order by count(*) desc;
Resource manager can have other potentially negative affects. If you're in a data warehouse, and using parallel queries, it's possible that resource manager has downgraded the queries on one system. If you're using parallel queries, try comparing the SQL monitoring reports from both systems:
select dbms_sqltune.report_sql_monitor(sql_id => '&YOUR_SQL_ID') from dual;
However, I have a feeling that you're using the wrong approach for your problem. There are generally two approaches to Oracle database performance - database tuning and query tuning. If you're only interested in a single query, then you should probably focus on things like the execution plan and the wait events for the operations of that specific query.
One of the job schedulers is running in the production environment on a daily basis which use to take only 20 mins based past execution history, but today it's been more than 2 hours still not completed.
a) How to check whether the SQL plan has changed today or not?
b) What could be the reasons for the plan change? One I know due to code change. What else could cause plan change?
You can check if the SQL execution plan has changed by using the Active Workload Repository (AWR). First, you need to find the SQL_ID for the relevant query. The view GV$SQL contains the most recent SQL. If you can't find the query in this view, try DBA_HIST_SQLTEXT instead.
select sql_id, sql_text
from gv$sql
where lower(sql_fulltext) like '%some unique string%';
With the SQL_ID, you can start investigating historical information. The table DBA_HIST_SQLSTAT contains lots of summary information about the SQL. The most important column is PLAN_HASH_VALUE; if that value changes, then the execution plan has changed.
select snap_id, sql_id, plan_hash_value, executions_delta, elapsed_time_delta/100000 seconds_delta
,dba_hist_sqlstat.*
from dba_hist_sqlstat
--join to dba_hist_snapshot if you want to find precise times instead of SNAP_IDs.
where sql_id = '&SQL_ID'
order by dba_hist_sqlstat.snap_id;
If the plan has changed, you can view both plans with this:
select * from table(dbms_xplan.display_awr(sql_id => '&SQL_ID'));
Unfortunately, the most difficult part of query tuning with Oracle is that there are a dozen different ways to view the execution plans, and each of them provides slightly different data.
This query only returns numbers for the last execution, but it returns actual numbers and times, which helps you focus on the specific operation and wait events that caused the problem.
select dbms_sqltune.report_sql_monitor(sql_id => '&SQL_ID', type => 'text') from dual;
This query returns some additional execution plan information, specifically the Note section. Most graphical IDEs leave out that section, but it's vital for complex troubleshooting. If something weird is going on, the Note section will often explain why.
select * from table(dbms_xplan.display_cursor(sql_id => '&SQL_ID'));
There are many reasons why execution plans can change. If you add additional information to the question I may be able to make an educated guess.
Quick Check :
Please check whether the Statistics, is upto Date, both System and Table statistics.
Pleae check if any changes to table or index made ?
I have sql hash value of a query.
I don't have the sqltext, plan hash or sql_id - only the hash value of the sql.
When I'm querying the v$sql view there are no result (I guess the sql is not in the memory already):
select * from v$sql where hash_value = 'hv_Example';
Is there a way to achieve the sql_id from the hash_value?
I didn't found a view that holds the hash value and the sql_id togather...
V$SQL contains both HASH_VALUE and SQL_ID, but not forever.
According to Tanel Poder's blog, the HASH_VALUE can be derived from the SQL_ID, but the inverse operation is not possible. But converting HASH_VALUE to SQL_ID wouldn't solve your problem anyway.
First of all, I'm not sure why you would have access to the HASH_VALUE but not the SQL_ID. The SQL_ID is much more commonly used for performance tuning. Whatever program or source is providing the HASH_VALUE should be modified to return the SQL_ID instead.
But the real problem here, whichever value you have, is that data is not permanently stored in V$SQL. As statements get old they are aged out of the shared pool, and disappear from V$SQL. Also, if you're using a clustered system, make sure you're using GV$SQL.
If you are using Enterprise Edition, and have licensed the Oracle Diagnostic Pack, you may be able to find historical SQL_ID values with one of these two statements:
select sql_id
from gv$active_session_history
where sql_full_plan_hash_value = 'XYZ';
select sql_id
from dba_hist_active_sess_history
where sql_full_plan_hash_value = 'XYZ';
Data in GV$ACTIVE_SESSION_HISTORY typically lasts for about a day. Data in DBA_HIST_* stays for 8 days by default, but is configurable. You can check the AWR retention with this query: select retention from dba_hist_wr_control;
If the HASH_VALUE is less old than the retention period, but still not in AWR, then you can probably ignore it. ASH and AWR use sampling, which means they do not capture everything that happens in a database. ASH takes a sample every second and AWR takes a sample every 10 seconds.
A lot of people struggle with this concept but it's helpful to come to terms with the idea of sampling. Systems that capture all of the information, like tracing everything, are overwhelming and use up too much space and processing power. If we're looking at performance problems then we do not care about something that doesn't happen for more than 10 seconds out of 8 days.
Just wondering if any of you people use Count(1) over Count(*) and if there is a noticeable difference in performance or if this is just a legacy habit that has been brought forward from days gone past?
The specific database is SQL Server 2005.
There is no difference.
Reason:
Books on-line says "COUNT ( { [ [ ALL | DISTINCT ] expression ] | * } )"
"1" is a non-null expression: so it's the same as COUNT(*).
The optimizer recognizes it for what it is: trivial.
The same as EXISTS (SELECT * ... or EXISTS (SELECT 1 ...
Example:
SELECT COUNT(1) FROM dbo.tab800krows
SELECT COUNT(1),FKID FROM dbo.tab800krows GROUP BY FKID
SELECT COUNT(*) FROM dbo.tab800krows
SELECT COUNT(*),FKID FROM dbo.tab800krows GROUP BY FKID
Same IO, same plan, the works
Edit, Aug 2011
Similar question on DBA.SE.
Edit, Dec 2011
COUNT(*) is mentioned specifically in ANSI-92 (look for "Scalar expressions 125")
Case:
a) If COUNT(*) is specified, then the result is the cardinality of T.
That is, the ANSI standard recognizes it as bleeding obvious what you mean. COUNT(1) has been optimized out by RDBMS vendors because of this superstition. Otherwise it would be evaluated as per ANSI
b) Otherwise, let TX be the single-column table that is the
result of applying the <value expression> to each row of T
and eliminating null values. If one or more null values are
eliminated, then a completion condition is raised: warning-
In SQL Server, these statements yield the same plans.
Contrary to the popular opinion, in Oracle they do too.
SYS_GUID() in Oracle is quite computation intensive function.
In my test database, t_even is a table with 1,000,000 rows
This query:
SELECT COUNT(SYS_GUID())
FROM t_even
runs for 48 seconds, since the function needs to evaluate each SYS_GUID() returned to make sure it's not a NULL.
However, this query:
SELECT COUNT(*)
FROM (
SELECT SYS_GUID()
FROM t_even
)
runs for but 2 seconds, since it doen't even try to evaluate SYS_GUID() (despite * being argument to COUNT(*))
I work on the SQL Server team and I can hopefully clarify a few points in this thread (I had not seen it previously, so I am sorry the engineering team has not done so previously).
First, there is no semantic difference between select count(1) from table vs. select count(*) from table. They return the same results in all cases (and it is a bug if not). As noted in the other answers, select count(column) from table is semantically different and does not always return the same results as count(*).
Second, with respect to performance, there are two aspects that would matter in SQL Server (and SQL Azure): compilation-time work and execution-time work. The Compilation time work is a trivially small amount of extra work in the current implementation. There is an expansion of the * to all columns in some cases followed by a reduction back to 1 column being output due to how some of the internal operations work in binding and optimization. I doubt it would show up in any measurable test, and it would likely get lost in the noise of all the other things that happen under the covers (such as auto-stats, xevent sessions, query store overhead, triggers, etc.). It is maybe a few thousand extra CPU instructions. So, count(1) does a tiny bit less work during compilation (which will usually happen once and the plan is cached across multiple subsequent executions). For execution time, assuming the plans are the same there should be no measurable difference. (One of the earlier examples shows a difference - it is most likely due to other factors on the machine if the plan is the same).
As to how the plan can potentially be different. These are extremely unlikely to happen, but it is potentially possible in the architecture of the current optimizer. SQL Server's optimizer works as a search program (think: computer program playing chess searching through various alternatives for different parts of the query and costing out the alternatives to find the cheapest plan in reasonable time). This search has a few limits on how it operates to keep query compilation finishing in reasonable time. For queries beyond the most trivial, there are phases of the search and they deal with tranches of queries based on how costly the optimizer thinks the query is to potentially execute. There are 3 main search phases, and each phase can run more aggressive(expensive) heuristics trying to find a cheaper plan than any prior solution. Ultimately, there is a decision process at the end of each phase that tries to determine whether it should return the plan it found so far or should it keep searching. This process uses the total time taken so far vs. the estimated cost of the best plan found so far. So, on different machines with different speeds of CPUs it is possible (albeit rare) to get different plans due to timing out in an earlier phase with a plan vs. continuing into the next search phase. There are also a few similar scenarios related to timing out of the last phase and potentially running out of memory on very, very expensive queries that consume all the memory on the machine (not usually a problem on 64-bit but it was a larger concern back on 32-bit servers). Ultimately, if you get a different plan the performance at runtime would differ. I don't think it is remotely likely that the difference in compilation time would EVER lead to any of these conditions happening.
Net-net: Please use whichever of the two you want as none of this matters in any practical form. (There are far, far larger factors that impact performance in SQL beyond this topic, honestly).
I hope this helps. I did write a book chapter about how the optimizer works but I don't know if its appropriate to post it here (as I get tiny royalties from it still I believe). So, instead of posting that I'll post a link to a talk I gave at SQLBits in the UK about how the optimizer works at a high level so you can see the different main phases of the search in a bit more detail if you want to learn about that. Here's the video link: https://sqlbits.com/Sessions/Event6/inside_the_sql_server_query_optimizer
Clearly, COUNT(*) and COUNT(1) will always return the same result. Therefore, if one were slower than the other it would effectively be due to an optimiser bug. Since both forms are used very frequently in queries, it would make no sense for a DBMS to allow such a bug to remain unfixed. Hence you will find that the performance of both forms is (probably) identical in all major SQL DBMSs.
In the SQL-92 Standard, COUNT(*) specifically means "the cardinality of the table expression" (could be a base table, `VIEW, derived table, CTE, etc).
I guess the idea was that COUNT(*) is easy to parse. Using any other expression requires the parser to ensure it doesn't reference any columns (COUNT('a') where a is a literal and COUNT(a) where a is a column can yield different results).
In the same vein, COUNT(*) can be easily picked out by a human coder familiar with the SQL Standards, a useful skill when working with more than one vendor's SQL offering.
Also, in the special case SELECT COUNT(*) FROM MyPersistedTable;, the thinking is the DBMS is likely to hold statistics for the cardinality of the table.
Therefore, because COUNT(1) and COUNT(*) are semantically equivalent, I use COUNT(*).
COUNT(*) and COUNT(1) are same in case of result and performance.
I would expect the optimiser to ensure there is no real difference outside weird edge cases.
As with anything, the only real way to tell is to measure your specific cases.
That said, I've always used COUNT(*).
As this question comes up again and again, here is one more answer. I hope to add something for beginners wondering about "best practice" here.
SELECT COUNT(*) FROM something counts records which is an easy task.
SELECT COUNT(1) FROM something retrieves a 1 per record and than counts the 1s that are not null, which is essentially counting records, only more complicated.
Having said this: Good dbms notice that the second statement will result in the same count as the first statement and re-interprete it accordingly, as not to do unnecessary work. So usually both statements will result in the same execution plan and take the same amount of time.
However from the point of readability you should use the first statement. You want to count records, so count records, not expressions. Use COUNT(expression) only when you want to count non-null occurences of something.
I ran a quick test on SQL Server 2012 on an 8 GB RAM hyper-v box. You can see the results for yourself. I was not running any other windowed application apart from SQL Server Management Studio while running these tests.
My table schema:
CREATE TABLE [dbo].[employee](
[Id] [bigint] IDENTITY(1,1) NOT NULL,
[Name] [nvarchar](50) NOT NULL,
CONSTRAINT [PK_employee] PRIMARY KEY CLUSTERED
(
[Id] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
GO
Total number of records in Employee table: 178090131 (~ 178 million rows)
First Query:
Set Statistics Time On
Go
Select Count(*) From Employee
Go
Set Statistics Time Off
Go
Result of First Query:
SQL Server parse and compile time:
CPU time = 0 ms, elapsed time = 35 ms.
(1 row(s) affected)
SQL Server Execution Times:
CPU time = 10766 ms, elapsed time = 70265 ms.
SQL Server parse and compile time:
CPU time = 0 ms, elapsed time = 0 ms.
Second Query:
Set Statistics Time On
Go
Select Count(1) From Employee
Go
Set Statistics Time Off
Go
Result of Second Query:
SQL Server parse and compile time:
CPU time = 14 ms, elapsed time = 14 ms.
(1 row(s) affected)
SQL Server Execution Times:
CPU time = 11031 ms, elapsed time = 70182 ms.
SQL Server parse and compile time:
CPU time = 0 ms, elapsed time = 0 ms.
You can notice there is a difference of 83 (= 70265 - 70182) milliseconds which can easily be attributed to exact system condition at the time queries are run. Also I did a single run, so this difference will become more accurate if I do several runs and do some averaging. If for such a huge data-set the difference is coming less than 100 milliseconds, then we can easily conclude that the two queries do not have any performance difference exhibited by the SQL Server Engine.
Note : RAM hits close to 100% usage in both the runs. I restarted SQL Server service before starting both the runs.
SET STATISTICS TIME ON
select count(1) from MyTable (nolock) -- table containing 1 million records.
SQL Server Execution Times:
CPU time = 31 ms, elapsed time = 36 ms.
select count(*) from MyTable (nolock) -- table containing 1 million records.
SQL Server Execution Times:
CPU time = 46 ms, elapsed time = 37 ms.
I've ran this hundreds of times, clearing cache every time.. The results vary from time to time as server load varies, but almost always count(*) has higher cpu time.
There is an article showing that the COUNT(1) on Oracle is just an alias to COUNT(*), with a proof about that.
I will quote some parts:
There is a part of the database software that is called “The
Optimizer”, which is defined in the official documentation as
“Built-in database software that determines the most efficient way to
execute a SQL statement“.
One of the components of the optimizer is called “the transformer”,
whose role is to determine whether it is advantageous to rewrite the
original SQL statement into a semantically equivalent SQL statement
that could be more efficient.
Would you like to see what the optimizer does when you write a query
using COUNT(1)?
With a user with ALTER SESSION privilege, you can put a tracefile_identifier, enable the optimizer tracing and run the COUNT(1) select, like: SELECT /* test-1 */ COUNT(1) FROM employees;.
After that, you need to localize the trace files, what can be done with SELECT VALUE FROM V$DIAG_INFO WHERE NAME = 'Diag Trace';. Later on the file, you will find:
SELECT COUNT(*) “COUNT(1)” FROM “COURSE”.”EMPLOYEES” “EMPLOYEES”
As you can see, it's just an alias for COUNT(*).
Another important comment: the COUNT(*) was really faster two decades ago on Oracle, before Oracle 7.3:
Count(1) has been rewritten in count(*) since 7.3 because Oracle like
to Auto-tune mythic statements. In earlier Oracle7, oracle had to
evaluate (1) for each row, as a function, before DETERMINISTIC and
NON-DETERMINISTIC exist.
So two decades ago, count(*) was faster
For another databases as Sql Server, it should be researched individually for each one.
I know that this question is specific for SQL Server, but the other questions on SO about the same subject (without mention a specific database) were closed and marked as duplicated from this answer.
In all RDBMS, the two ways of counting are equivalent in terms of what result they produce. Regarding performance, I have not observed any performance difference in SQL Server, but it may be worth pointing out that some RDBMS, e.g. PostgreSQL 11, have less optimal implementations for COUNT(1) as they check for the argument expression's nullability as can be seen in this post.
I've found a 10% performance difference for 1M rows when running:
-- Faster
SELECT COUNT(*) FROM t;
-- 10% slower
SELECT COUNT(1) FROM t;
COUNT(1) is not substantially different from COUNT(*), if at all. As to the question of COUNTing NULLable COLUMNs, this can be straightforward to demo the differences between COUNT(*) and COUNT(<some col>)--
USE tempdb;
GO
IF OBJECT_ID( N'dbo.Blitzen', N'U') IS NOT NULL DROP TABLE dbo.Blitzen;
GO
CREATE TABLE dbo.Blitzen (ID INT NULL, Somelala CHAR(1) NULL);
INSERT dbo.Blitzen SELECT 1, 'A';
INSERT dbo.Blitzen SELECT NULL, NULL;
INSERT dbo.Blitzen SELECT NULL, 'A';
INSERT dbo.Blitzen SELECT 1, NULL;
SELECT COUNT(*), COUNT(1), COUNT(ID), COUNT(Somelala) FROM dbo.Blitzen;
GO
DROP TABLE dbo.Blitzen;
GO