Consider table testTable, a table with six fields: one of them a UNIQUEIDENTIFIER, one a TIMESTAMP and four of them VARCHARs. Field Filename is VARCHAR.
This first query takes 1 minutes 38 seconds
Select top 1 * from testTable WHERE Filename = 'any.string.1512.b'
Either of these queries takes 1-3 seconds
Select top 1 * from testTable WHERE Filename = 'any.string.1512'
Select top 1 * from testTable WHERE Filename like 'cusip.realloc.1412.b%'
I have looked at the execution plan for all three and the only difference is that the last query (the LIKE statement) used 46% index seek\54% Key Lookup vs a 50\50 index\key lookup for the first two. As far as I can tell as soon as I no longer use the .b part of this search criterium, the queries go back to normal speed.
FileName has been indexed; table has been removed and recreated just in case. We have added indexes, removed indexes, check table, checked database, restart services, restart server, recreated the table. This field used to be VARCHAR(MAX) and I changed it to VARCHAR(100) to index it, but the problem was occurring before making this change.
Something else that I believe may be happening is that there might be something wrong with the end of the table. It will never complete a full:
Select * from testTable
I hoped it was a corrupted table but that wasn't the case. However when we attempt to generate a script in SSMS it fails to generate (no error given). I was able to recreate it by using another SQL client and generating the structure from SSMS and data copy from the other SQL client.
We are pretty stumped.
It's been several years since I've worked with SQL and C# .NET so be gentle.
I'm jumping in to assist on a project that a coworker has been building. Something though seems quite out of whack.
I'm trying to provide straight reports on a particular Table in the database. It has 9 columns and approximately 1.6M rows last time I checked. This is big, but it's hardly large enough to create problems. However, when I run a simple Query using MS SQL Server Management Studio, it takes 11 seconds.
SELECT *
FROM [4.0Analytics].[dbo].[Measurement]
where VIN = 'JTHBJ46G482271076';
I tried creating an index for VIN but it times out.
"An exception occurred while executing a Transact-SQL statement or batch."
"Could not allocate space for object 'X' in dabase 'Your Datase' because the 'PRIMARY' filegroup is full"
It seems however that it should be taking a lot less time in the first place even non-indexed so I'd like to find out what might be wrong there and then move onto the index time-out next. Unless 11 seconds is normal for a simple query when non-indexed?
As David Gugg has mentioned you do not have enough space left in your database.
Check if you have enough space left on the disk where your Primary File is located. If you have enough space on the disk use the following command and then try to create the index
USE [master]
GO
ALTER DATABASE [4.0Analytics]
MODIFY FILE ( NAME = N'Primary_File_Name'
, MAXSIZE = UNLIMITED
, FILEGROWTH = 10%
)
GO
-- This will allow your database to grow automatically if it runs out of space
-- provided you have space left on the disk
-- Now try to create the Index and it should let you create it.
SELECT * is taking too long. Well no wonder how many indexes you put on a table if you are doing a SELECT * it will always result in a Clustered Index Scan if you have primary key defined on the table otherwise a table scan.
Try `Select <Column Names>` --<-- Only the columns you actually need
I would not recommend to SET the datafile Autogruth to percentage [%], it is better
(best practice ) to set it to growth by MB, for example:
USE [master]
GO
ALTER DATABASE [YourDataBaseName] MODIFY
FILE ( NAME = N'YouDataBaseFileName',
FILEGROWTH = 10240KB ,
MAXSIZE = UNLIMITED)
GO
The Error you have got during the index creation were, because that the index didn't have the ability to extend.(because the parameter MAXSIZE is set to LIMIT value).
to check it you can do by :
a. Object Explorer >>> Databases >>> Right click on the requested Database >>> GO to TAB "File".
b.T-SQL :
select
FILE_NAME(e.file_id ) as [FileName],
e.growth,
e.max_size,
e.is_percent_growth
f rom sys.master_files e
where OBJECT_NAME(e.database_id) = 'YourDatabaseName'
GO
I'm in the process of importing data from a legacy MySQL database into SQL Server 2005.
I have one table in particular that's causing me grief. I've imported it from MySQL using a linked server and the MySQL ODBC driver, and I end up with this:
Col Name Datatype MaxLen
OrderItem_ID bigint 8
PDM_Structure_ID int 4
LastModifiedDate datetime 8
LastModifiedUser varchar 20
CreationDate datetime 8
CreationUser varchar 20
XMLData text -1
OrderHeader_ID bigint 8
Contract_Action varchar 10
ContractItem int 4
My main focus is on the XMLData column - I need to clean it up and make it so that I can convert it to an XML datatype to use XQuery on it.
So I set the table option "large data out of row" to 1:
EXEC sp_tableoption 'OrderItem', 'large value types out of row', 1
and then I go ahead and convert XMLData to VARCHAR(MAX) and do some cleanup of the XML stored in that field. All fine so far.
But when I now try to convert that column to XML datatype:
ALTER TABLE dbo.OrderItem
ALTER COLUMN XMLData XML
I get this message here:
Msg 511, Level 16, State 1, Line 1
Cannot create a row of size 8077 which
is greater than the allowable maximum
row size of 8060. The statement has
been terminated.
which is rather surprising, seeing that the columns besides the XMLData only make up roughly 90 bytes, and I specifically instructed SQL Server to store all "large data" off-row....
So why on earth does SQL Server refuse to convert that column to XML data??? Any ideas?? Thoughts?? Things I can check / change in my approach??
Update: I don't know what changed, but on a second attempt to import the raw data from MySQL into SQL Server, I was successfully able to convert that NTEXT -> VARCHAR(MAX) column to XML in the end..... odd..... anyhoo - works now - thanks guys for all your input and recommendations! Highly appreciated !
If you have sufficient storage space, you could try selecting from the VARCHAR(MAX) version of the table into a new table with the same schema but with XMLData set up as XML - either using SELECT INTO or by explicitly creating the table before you begin.
PS - it's a side issue unrelated to your problem, but you might want to check that you're not losing Unicode characters in the original MySQL XMLData field by this conversion since the text/varchar data types won't support them.
Can you ADD a new column of type xml?
If so, add the new xml column, update the table to set the new column equal to the XmlData column and then drop the XmlData column.
Edit
I have a table "TestTable" with a "nvarchar(max)" column.
select * from sys.tables where name = 'TestTable'
This gives a result containing:
[lob_data_space_id] [text_in_row_limit] [large_value_types_out_of_row]
1 0 0
yet I can happily save 500k characters in my nvarchar(max) field.
What do you get if you query sys.tables for your OrderItems table?
If your [text_in_row_limit] is not zero, try this, which should convert any existing in-row strings into BLOBs:
exec sp_tableoption 'OrderItems', 'text in row', 0
and then try to switch from nvarchar(max) to xml.
From BOL,
Disabling the text in row option or
reducing the limit of the option will
require the conversion of all BLOBs;
therefore, the process can be long,
depending on the number of BLOB
strings that must be converted. The
table is locked during the conversion
process.
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I'm surprised this hasn't been posted yet. Any interesting tricks that you know about in Postgres? Obscure config options and scaling/perf tricks are particularly welcome.
I'm sure we can beat the 9 comments on the corresponding MySQL thread :)
Since postgres is a lot more sane than MySQL, there are not that many "tricks" to report on ;-)
The manual has some nice performance tips.
A few other performance related things to keep in mind:
Make sure autovacuum is turned on
Make sure you've gone through your postgres.conf (effective cache size, shared buffers, work mem ... lots of options there to tune).
Use pgpool or pgbouncer to keep your "real" database connections to a minimum
Learn how EXPLAIN and EXPLAIN ANALYZE works. Learn to read the output.
CLUSTER sorts data on disk according to an index. Can dramatically improve performance of large (mostly) read-only tables. Clustering is a one-time operation: when the table is subsequently updated, the changes are not clustered.
Here's a few things I've found useful that aren't config or performance related per se.
To see what's currently happening:
select * from pg_stat_activity;
Search misc functions:
select * from pg_proc WHERE proname ~* '^pg_.*'
Find size of database:
select pg_database_size('postgres');
select pg_size_pretty(pg_database_size('postgres'));
Find size of all databases:
select datname, pg_size_pretty(pg_database_size(datname)) as size
from pg_database;
Find size of tables and indexes:
select pg_size_pretty(pg_relation_size('public.customer'));
Or, to list all tables and indexes (probably easier to make a view of this):
select schemaname, relname,
pg_size_pretty(pg_relation_size(schemaname || '.' || relname)) as size
from (select schemaname, relname, 'table' as type
from pg_stat_user_tables
union all
select schemaname, relname, 'index' as type
from pg_stat_user_indexes) x;
Oh, and you can nest transactions, rollback partial transactions++
test=# begin;
BEGIN
test=# select count(*) from customer where name='test';
count
-------
0
(1 row)
test=# insert into customer (name) values ('test');
INSERT 0 1
test=# savepoint foo;
SAVEPOINT
test=# update customer set name='john';
UPDATE 3
test=# rollback to savepoint foo;
ROLLBACK
test=# commit;
COMMIT
test=# select count(*) from customer where name='test';
count
-------
1
(1 row)
The easiest trick to let postgresql perform a lot better (apart from setting and using proper indexes of course) is just to give it more RAM to work with (if you have not done so already). On most default installations the value for shared_buffers is way too low (in my opinion). You can set
shared_buffers
in postgresql.conf. Divide this number by 128 to get an approximation of the amount of memory (in MB) postgres can claim. If you up it enough this will make postgresql fly. Don't forget to restart postgresql.
On Linux systems, when postgresql won't start again you will probably have hit the kernel.shmmax limit. Set it higher with
sysctl -w kernel.shmmax=xxxx
To make this persist between boots, add a kernel.shmmax entry to /etc/sysctl.conf.
A whole bunch of Postgresql tricks can be found here:
http://www.postgres.cz/index.php/PostgreSQL_SQL_Tricks
Postgres has a very powerful datetime handling facility thanks to its INTERVAL support.
For example:
select NOW(), NOW() + '1 hour';
now | ?column?
-------------------------------+-------------------------------
2009-04-18 01:37:49.116614+00 | 2009-04-18 02:37:49.116614+00
(1 row)
select current_date ,(current_date + interval '1 year')::date;
date | date
---------------------+----------------
2014-10-17 | 2015-10-17
(1 row)
You can cast many strings to an INTERVAL type.
COPY
I'll start. Whenever I switch to Postgres from SQLite, I usually have some really big datasets. The key is to load your tables with COPY FROM rather than doing INSERTS. See documentation:
http://www.postgresql.org/docs/8.1/static/sql-copy.html
The following example copies a table to the client using the vertical bar (|) as the field delimiter:
COPY country TO STDOUT WITH DELIMITER '|';
To copy data from a file into the country table:
COPY country FROM '/usr1/proj/bray/sql/country_data';
See also here:
Faster bulk inserts in sqlite3?
My by far favorite is generate_series: at last a clean way to generate dummy rowsets.
Ability to use a correlated value in a LIMIT clause of a subquery:
SELECT (
SELECT exp_word
FROM mytable
OFFSET id
LIMIT 1
)
FROM othertable
Abitlity to use multiple parameters in custom aggregates (not covered by the documentation): see the article in my blog for an example.
One of the things I really like about Postgres is some of the data types supported in columns. For example, there are column types made for storing Network Addresses and Arrays. The corresponding functions (Network Addresses / Arrays) for these column types let you do a lot of complex operations inside queries that you'd have to do by processing results through code in MySQL or other database engines.
Arrays are really cool once you get to know 'em.
Lets say you would like to store some hyper links between pages. You might start by thinking about creating a Table kinda like this:
CREATE TABLE hyper.links (
tail INT4,
head INT4
);
If you needed to index the tail column, and you had, say 200,000,000 links-rows (like wikipedia would give you), you would find yourself with a huge Table and a huge Index.
However, with PostgreSQL, you could use this Table format instead:
CREATE TABLE hyper.links (
tail INT4,
head INT4[],
PRIMARY KEY(tail)
);
To get all heads for a link you could send a command like this (unnest() is standard since 8.4):
SELECT unnest(head) FROM hyper.links WHERE tail = $1;
This query is surprisingly fast when it is compared with the first option (unnest() is fast and the Index is way way smaller). Furthermore, your Table and Index will take up much less RAM-memory and HD-space, especially when your Arrays are so long that they are compressed to a Toast Table. Arrays are really powerful.
Note: while unnest() will generate rows out of an Array, array_agg() will aggregate rows into an Array.
Materialized Views are pretty easy to setup:
CREATE VIEW my_view AS SELECT id, AVG(my_col) FROM my_table GROUP BY id;
CREATE TABLE my_matview AS SELECT * FROM my_view;
That creates a new table, my_matview, with the columns and values of my_view. Triggers or a cron script can then be setup to keep the data up to date, or if you're lazy:
TRUNCATE my_matview;
INSERT INTO my_matview SELECT * FROM my_view;
Inheritance..infact Multiple Inheritance (as in parent-child "inheritance" not 1-to-1 relation inheritance which many web frameworks implement when working with postgres).
PostGIS (spatial extension), a wonderful add-on that offers comprehensive set of geometry functions and coordinates storage out of the box. Widely used in many open-source geo libs (e.g. OpenLayers,MapServer,Mapnik etc) and definitely way better than MySQL's spatial extensions.
Writing procedures in different languages e.g. C, Python,Perl etc (makes your life easir to code if you're a developer and not a db-admin).
Also all procedures can be stored externally (as modules) and can be called or imported at runtime by specified arguments. That way you can source control the code and debug the code easily.
A huge and comprehensive catalogue on all objects implemented in your database (i.e. tables,constraints,indexes,etc).
I always find it immensely helpful to run few queries and get all meta info e.g. ,constraint names and fields on which they have been implemented on, index names etc.
For me it all becomes extremely handy when I have to load new data or do massive updates in big tables (I would automatically disable triggers and drop indexes) and then recreate them again easily after processing has finished. Someone did an excellent job of writing handful of these queries.
http://www.alberton.info/postgresql_meta_info.html
Multiple schemas under one database, you can use it if your database has large number of tables, you can think of schemas as categories. All tables (regardless of it's schema) have access to all other tables and functions present in parent db.
You don't need to learn how to decipher "explain analyze" output, there is a tool: http://explain.depesz.com
select pg_size_pretty(200 * 1024)
pgcrypto: more cryptographic functions than many programming languages' crypto modules provide, all accessible direct from the database. It makes cryptographic stuff incredibly easy to Just Get Right.
A database can be copied with:
createdb -T old_db new_db
The documentation says:
this is not (yet) intended as a general-purpose "COPY DATABASE" facility
but it works well for me and is much faster than
createdb new_db
pg_dump old_db | psql new_db
Memory storage for throw-away data/global variables
You can create a tablespace that lives in the RAM, and tables (possibly unlogged, in 9.1) in that tablespace to store throw-away data/global variables that you'd like to share across sessions.
http://magazine.redhat.com/2007/12/12/tip-from-an-rhce-memory-storage-on-postgresql/
Advisory locks
These are documented in an obscure area of the manual:
http://www.postgresql.org/docs/9.0/interactive/functions-admin.html
It's occasionally faster than acquiring multitudes of row-level locks, and they can be used to work around cases where FOR UPDATE isn't implemented (such as recursive CTE queries).
This is my favorites list of lesser know features.
Transactional DDL
Nearly every SQL statement is transactional in Postgres. If you turn off autocommit the following is possible:
drop table customer_orders;
rollback;
select *
from customer_orders;
Range types and exclusion constraint
To my knowledge Postgres is the only RDBMS that lets you create a constraint that checks if two ranges overlap. An example is a table that contains product prices with a "valid from" and "valid until" date:
create table product_price
(
price_id serial not null primary key,
product_id integer not null references products,
price numeric(16,4) not null,
valid_during daterange not null
);
NoSQL features
The hstore extension offers a flexible and very fast key/value store that can be used when parts of the database need to be "schema-less". JSON is another option to store data in a schema-less fashion and
insert into product_price
(product_id, price, valid_during)
values
(1, 100.0, '[2013-01-01,2014-01-01)'),
(1, 90.0, '[2014-01-01,)');
-- querying is simply and can use an index on the valid_during column
select price
from product_price
where product_id = 42
and valid_during #> date '2014-10-17';
The execution plan for the above on a table with 700.000 rows:
Index Scan using check_price_range on public.product_price (cost=0.29..3.29 rows=1 width=6) (actual time=0.605..0.728 rows=1 loops=1)
Output: price
Index Cond: ((product_price.valid_during #> '2014-10-17'::date) AND (product_price.product_id = 42))
Buffers: shared hit=17
Total runtime: 0.772 ms
To avoid inserting rows with overlapping validity ranges a simple (and efficient) unique constraint can be defined:
alter table product_price
add constraint check_price_range
exclude using gist (product_id with =, valid_during with &&)
Infinity
Instead of requiring a "real" date far in the future Postgres can compare dates to infinity. E.g. when not using a date range you can do the following
insert into product_price
(product_id, price, valid_from, valid_until)
values
(1, 90.0, date '2014-01-01', date 'infinity');
Writeable common table expressions
You can delete, insert and select in a single statement:
with old_orders as (
delete from orders
where order_date < current_date - interval '10' year
returning *
), archived_rows as (
insert into archived_orders
select *
from old_orders
returning *
)
select *
from archived_rows;
The above will delete all orders older than 10 years, move them to the archived_orders table and then display the rows that were moved.
1.) When you need append notice to query, you can use nested comment
SELECT /* my comments, that I would to see in PostgreSQL log */
a, b, c
FROM mytab;
2.) Remove Trailing spaces from all the text and varchar field in a database.
do $$
declare
selectrow record;
begin
for selectrow in
select
'UPDATE '||c.table_name||' SET '||c.COLUMN_NAME||'=TRIM('||c.COLUMN_NAME||') WHERE '||c.COLUMN_NAME||' ILIKE ''% '' ' as script
from (
select
table_name,COLUMN_NAME
from
INFORMATION_SCHEMA.COLUMNS
where
table_name LIKE 'tbl%' and (data_type='text' or data_type='character varying' )
) c
loop
execute selectrow.script;
end loop;
end;
$$;
3.) We can use a window function for very effective removing of duplicate rows:
DELETE FROM tab
WHERE id IN (SELECT id
FROM (SELECT row_number() OVER (PARTITION BY column_with_duplicate_values), id
FROM tab) x
WHERE x.row_number > 1);
Some PostgreSQL's optimized version (with ctid):
DELETE FROM tab
WHERE ctid = ANY(ARRAY(SELECT ctid
FROM (SELECT row_number() OVER (PARTITION BY column_with_duplicate_values), ctid
FROM tab) x
WHERE x.row_number > 1));
4.) When we need to identify server's state, then we can use a function:
SELECT pg_is_in_recovery();
5.) Get functions's DDL command.
select pg_get_functiondef((select oid from pg_proc where proname = 'f1'));
6.) Safely changing column data type in PostgreSQL
create table test(id varchar );
insert into test values('1');
insert into test values('11');
insert into test values('12');
select * from test
--Result--
id
character varying
--------------------------
1
11
12
You can see from the above table that I have used the data type – ‘character varying’ for ‘id’
column. But it was a mistake, because I am always giving integers as id. So using varchar here is a
bad practice. So let’s try to change the column type to integer.
ALTER TABLE test ALTER COLUMN id TYPE integer;
But it returns:
ERROR: column “id” cannot be cast automatically to type integer SQL
state: 42804 Hint: Specify a USING expression to perform the
conversion
That means we can’t simply change the data type because data is already there in the column. Since the data is of type ‘character varying’ postgres cant expect it as integer though we entered integers only. So now, as postgres suggested we can use the ‘USING’ expression to cast our data into integers.
ALTER TABLE test ALTER COLUMN id TYPE integer USING (id ::integer);
It Works.
7.) Know who is connected to the Database
This is more or less a monitoring command. To know which user connected to which database
including their IP and Port use the following SQL:
SELECT datname,usename,client_addr,client_port FROM pg_stat_activity ;
8.) Reloading PostgreSQL Configuration files without Restarting Server
PostgreSQL configuration parameters are located in special files like postgresql.conf and pg_hba.conf. Often, you may need to change these parameters. But for some parameters to take effect we often need to reload the configuration file. Of course, restarting server will do it. But in a production environment it is not preferred to restarting the database, which is being used by thousands, just for setting some parameters. In such situations, we can reload the configuration files without restarting the server by using the following function:
select pg_reload_conf();
Remember, this wont work for all the parameters, some parameter
changes need a full restart of the server to be take in effect.
9.) Getting the data directory path of the current Database cluster
It is possible that in a system, multiple instances(cluster) of PostgreSQL is set up, generally, in different ports or so. In such cases, finding which directory(physical storage directory) is used by which instance is a hectic task. In such cases, we can use the following command in any database in the cluster of our interest to get the directory path:
SHOW data_directory;
The same function can be used to change the data directory of the cluster, but it requires a server restarts:
SET data_directory to new_directory_path;
10.) Find a CHAR is DATE or not
create or replace function is_date(s varchar) returns boolean as $$
begin
perform s::date;
return true;
exception when others then
return false;
end;
$$ language plpgsql;
Usage: the following will return True
select is_date('12-12-2014')
select is_date('12/12/2014')
select is_date('20141212')
select is_date('2014.12.12')
select is_date('2014,12,12')
11.) Change the owner in PostgreSQL
REASSIGN OWNED BY sa TO postgres;
12.) PGADMIN PLPGSQL DEBUGGER
Well explained here
It's convenient to rename an old database rather than mysql can do. Just using the following command:
ALTER DATABASE name RENAME TO new_name