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 ?
Assuming I execute a query like the one below in Oracle;
SELECT t1.check_in,t1.check_out, t1.room_id,t2.room_name
FROM mydb.reservation_tb as t1
LEFT JOIN mydb.rooms_tb as t2 on t1.room_id = t2.room_id
WHERE t1.check_in = '2012-08-01' and t1.check_out = '2012-08-08' and t1.room_id = 12
I want to know if there is a way I can determine the amount of Memory and CPU time that were utilized by this query when it executed in ORACLE.
The below queries can find the CPU and memory for a query.
The dynamic performance views are tricky and can take a while to get used to. They may contain results from multiple runs and they will age out over time.
--1. First run the query, if it hasn't already been run.
select ...
--2. Find the SQL_ID by searching for some unique text in the query:
select sql_id, sql_fulltext from gv$sql where lower(sql_fulltext) like '%unique string%';
--3. Find the amount of CPU time used by this query.
--GV$SQL is based on the shared_pool, it may contain the time for multiple runs
--in the "recent past", usually the past few hours or days.
--The data can be flushed with: alter system flush shared_pool;
select cpu_time/1000000 cpu_seconds, gv$sql.*
from gv$sql
where sql_id = 'f6krg7hkt08k2';
--4. The memory and temporary tablespace used by a query.
--This only counts memory and temporary tablespace used for things like sorting and hashing.
--There's no easy way to tell how a query is affecting the buffer cache.
--(Calculating for a parallel query may require different aggregation.)
--GV$ACTIVE_SESSION_HISTORY also contains temporary samples and will usually only
--have data for the past few hours or days.
select
max(pga_allocated/1024/1024/1024) max_pga_allocated_gb,
max(temp_space_allocated/1024/1024/1024) max_temp_space_allocated_gb
from gv$active_session_history
where sql_id = 'f6krg7hkt08k2'
Also I recommend you change '2012-08-01' to date '2012-08-01'. Without the keyword date the query is using a date format that depends on the user's session settings. With the date keyword the string is now a date literal and conforms to ISO 8601 and will work on any client.
In oracle, working with JDBC from Java, I am trying to optimize a specific query:
select sql_fulltext from v$sql where last_active_time > ?
(? = Some recent date)
The query run time in 1.8 seconds, even if there are no results.
I am wondering how I can I improve it.
The best thing would be if I had an INDEX on last_active_time, but its a view.
My questions is:
How can I improve the running time of the query?
Are there any possible hints I can send?
Is it possible to create a materialized view on this view, and somehow have that indexed?
Any suggestions would be appreciated.
Thanks
V$SQL is known to be somewhat slow. It is to a large extent a memory structure that you are querying there. If you are concerned about performance (and impact on the system) you should use V$SQLSTATS instead.
Quote from the manual
The column definitions for columns in V$SQLSTATS are identical to those in the V$SQL and V$SQLAREA views. However, the V$SQLSTATS view differs from V$SQL and V$SQLAREA in that it is faster, more scalable, and has a greater data retention
(Emphasis mine)
There is however a drawback: V$SQLSTATS does not contain all the columns from V$SQL but it does contain the SQL_FULLTEXT column, so it should be OK for your use-case
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
My question is similar to the one posed in this thread:
How to avoid this very heavy query that slows down the application?
We checked for missing indexes on foreign keys and found some. Adding the missing indexes actually had the opposite effect in that it slowed the query even more. One important piece of information is that our customer has a single Oracle install with our schema replicated on it 21 times. Each schema has just shy of 1,000 tables in it. Are we asking too much of Oracle with such a large number of tables (and of course indexes)? I don't know what their hardware is but my question is whether this is a reasonable approach or would it be be better to break up the users to different SIDs?
Below is the query that is being executed by Hibernate. The customer is telling us that this query is consuming about 45% of the processor when it is being executed (though I don't know for how long).
Any suggestions are appreciated,
Steve
SELECT NULL AS table_cat,
owner AS table_schem,
table_name,
0 AS non_unique,
NULL AS index_qualifier,
NULL AS index_name,
0 AS TYPE,
0 AS ordinal_position,
NULL AS column_name,
NULL AS asc_or_desc,
num_rows AS CARDINALITY,
blocks AS pages,
NULL AS filter_condition
FROM all_tables
WHERE table_name = 'BOOKING'
AND owner = 'FORWARD_TN'
UNION
SELECT NULL AS table_cat,
i.owner AS table_schem,
i.table_name,
DECODE (i.uniqueness, 'UNIQUE', 0, 1),
NULL AS index_qualifier,
i.index_name,
1 AS TYPE,
c.column_position AS ordinal_position,
c.column_name,
NULL AS asc_or_desc,
i.distinct_keys AS CARDINALITY,
i.leaf_blocks AS pages,
NULL AS filter_condition
FROM all_indexes i,
all_ind_columns c
WHERE i.table_name = 'BOOKING'
AND i.owner = 'FORWARD_TN'
AND i.index_name = c.index_name
AND i.table_owner = c.table_owner
AND i.table_name = c.table_name
AND i.owner = c.index_owner
ORDER BY non_unique,
TYPE,
index_name,
ordinal_position
You're not hitting any kind of capacity issue with 1,000 tables. That's still relatively small in the Oracle world. Just doing a quick check of our E-Business Suite install and it has 23,000 tables. A query using up a ton of CPU is almost always an execution plan problem. Some things to look at
Have you collected optimizer statistics? Without them the optimizer may be making a really poor decision on how to execute the query.
The next step is to look the execution plan itself. If you have the enterprise manager running, it probably has that query right up on the front page for consuming resources. You can just click on it and see what it's doing. Without that you have to use sql_trace or explain plan to see what's happening.
You could be easily hit by excessive parse time on the Oracle server if all of your statements use slightly different, literal SQL (i.e. no bind variables) for each of the 22.000 tables. If this is the case, just switch to bind variables and the CPU consumption should lower substantially.
Can your customer tell in what Oracle function the CPU time is spent? Oracle offers the neccessary statistics. As the CPU consumption is reported to be a significant part of the whole instance's consumption, your customer could run a statspack report (or ASH if he has licensed the diagnostic pack). That should show where exactly the CPU time is being spent.
Our customer reviewed their Oracle configuration and changed the configuration to the following values:
optimizer_index_caching=90
optimizer_index_cost_adj=15
optimizer_mode='CHOOSE'
They report that this seems to have fixed their speed issue.