In Sql Server there's sys Schema. sys.Columns, sys.Tables.
I have a general tables which I need to rename to SysUsers, SysRoles, etc.
Is it fine to do that? I will not use Sys schema. I just will prefix tables with Sys
I find SQL Server itself do it generally
select * FROM SysColumns // NOTE its not sys.Columns
TL;DR: Don't do this.
You will have name clashes and your objects will be unusable.
I strongly recommend against this. If you have any objects where the names clashes you will not be able to reference it.
Take this simple example:
USE master;
GO
CREATE DATABASE Sillytest;
GO
USE Sillytest;
GO
SELECT *
FROM syscolumns;
GO
SELECT *
FROM dbo.syscolumns;
GO
SELECT *
FROM sys.syscolumns;
GO
CREATE TABLE dbo.syscolumns (ID int, ColumnName sysname);
GO
SELECT *
FROM syscolumns;
GO
SELECT *
FROM dbo.syscolumns;
GO
SELECT *
FROM sys.syscolumns;
GO
USE master;
GO
DROP DATABASE Sillytest;
GO
Every single reference to syscolumns, whether prefixed by dbo, sys, or not at all, references the object sys.syscolumns. Not one of those statements returns data from the (empty) user table I created dbo.syscolumns. Notice, as well, that the reference to dbo.syscolumns before I create a table of that name also works.
Yes, you can create the objects, but if the name already exists as a sys.sys{object} object, then you won't be able to use it.
Further to this, there is already an object sys.sysusers, so we actually have the answer; don't do it, you already have a clash.
Total agreement with #Larnu and I upvoted that answer. Let me add one more.
By putting a single prefix at the front of all your table names, you actually hurt your ability to search, sort, and filter, your tables. It will slow down the database. It will hurt SSMS behavior and 3rd party tools.
Don't do this, but also, don't do it with something else either; tbl, tab, none of that junk.
In the SQL Server 2008 database I have a user-defined data type. In one of stored procs I was going to use that type as a column type of temp table, like:
CREATE TABLE #SomeTable
(
[some_column] UDT_SomeType,
-- other columns
)
Apparently my attempt failed, because, as far as I googled, my UDT_SomeType does not exist in tempdb (where temp table is actually stored).
The UDT_SomeType is actually NUMERIC(19,9), so I can use the following workaround for now:
CREATE TABLE #SomeTable
(
[some_column] NUMERIC(19,9),
-- others columns
)
However I don't think it is a really good solution. Is there any kind of best practice which can be applied here?
Important Information:
This workaround should never be used in any SP or structured query; its only usage should be limited to temporary queries in a protected environment to avoid any possible drawback. It has been written just to demonstrate that in special cases it would be possible to have UDTs in temp tables. Thanks to #Marcel (see comment) for having pointed it out.
Unfortunately is not really straightforward but with some script you can, I would keep a small script to create all those needed types to be launched when necessary.
Aux script:
USE [tempdb]
GO
CREATE TYPE [UDT_SomeType] FROM NUMERIC(19,9)
GO
Normal script:
USE [YOURDB]
GO
CREATE TABLE #SomeTable
(
[some_column] UDT_SomeType,
-- other columns
)
I have the following scenario/requirements for which I am not sure what is the best way to address to perform in the fastest way possible, looking for some guidance of features to use and examples of them, if available
I will receive anywhere between 10k to 100k of entities (in XML format) from a web service that I want to upsert (some rows might exist, others might not).
here are some of the requirements:
The source of the XML is a web service that I'm calling from C# code. Actually two different methods. For one of the methods, the return schema will be something flat that I can map directly to one of my tables. For the other, it will return an XML representation that I might need to work with in C# in order to be able to map it to flat entities for my tables. In that scenario, would it be best to do the modifications needed and then write to file to an XML to use as source?
The returned XML can contain up to 150k entities in XML, that may or may not exist in my tables yet, so I'm looking to upsert them. The files, when written to disk, can weight up to 20 megabytes. I asked if they could do JSON instead of XML, but apparently that's not a choice.
The SQL database is on a different server than my IIS server, so I rather avoid having the SQL server retrieve the XML from a file, I rather pass it from C# as a string or as a Table Value Parameter.
The tables are rather simple and don't have indexes other than the PK ones.
I've never been big on XML, although it got way easier with LINQ to XML, which I was initially using to parse each record and send individual inserts but the performance was just bad, so based on some research I've been doing, I'm thinking I could use:
Upserts from SQL server through MERGE statements.
Pass the whole XML as a parameter and use OPENXML to use as source in the MERGE statement.
Or, somehow generate a Table Value Parameter in C# and pass that to SQL to use on the MERGE.
I read on this similar question (which didnt have access to upsert/merge) that instead of trying to upsert directly from the XML, that it might be better to insert everything to a temporary table and do the merge/upsert against the temporary table?
Would this work and be considerably fast?
If anyone has had a similar scenario, can you share your thoughts/ideas about what combination of features would be best?
Thanks.
You are on the right track. I have a similar setup using XML to transfer data between an online portal and the client-server application. The rest of the setup is very similar to what you have.
The fact that your tables are not indexed is a bit of a concern, if you are comparing any fields that are not PK Fields, regardless of how you index the temp tables. It is important to have either one index with all of the fields used in the merge match clause, or an index for each of them - I find the former yields better performance. Beyond that, using an XML parameter, OpenXML and temp tables is the way to go.
The following code has not been tested, so may need a bit of debugging, but it will put you on the right track. A couple of notes: If all of the fields in the OpenXML WITH clause are attributes, then you can drop the last parameter (i.e. ", 2") and field source specifiers (i.e. "#id" for the detail table). Although the data in your description is flat, in which case you will only need one table, I do often need to import into linked records. I have included a simple master-detail relationship example in the code below, just for the sake of completeness.
CREATE PROCEDURE usp_ImportFromXML (#data XML) AS
BEGIN
/*
<root>
<data>
<match_field_1>1</match_field_1>
<match_field_2>val2</match_field_2>
<data_1>val3</data_1>
<data_2>val4</data_2>
<detail_records>
<detail_data id="detailID1">
<detail_1>blah1<detail_1>
<detail_2>blah2<detail_2>
</detail_data>
<detail_data id="detailID2">
<detail_1>blah3<detail_1>
<detail_2>blah4<detail_2>
</detail_data>
</detail_records>
</data>
<data>
...
</root>
*/
DECLARE #iDoc INT
EXEC sp_xml_preparedocument #iDoc OUTPUT, #data
SELECT * INTO #temp
FROM OpenXML(#iDoc, '/root/data', 2) WITH (
match_field_1 INT,
match_field_2 VARCHAR(50),
data_1 VARCHAR(50),
data_2 VARCHAR(50)
)
SELECT * INTO #detail
FROM OpenXML(#iDoc, '/root/data/detail_data', 2) WITH (
match_field_1 INT '../../match_field_1',
match_field_2 VARCHAR(50) '../../match_field_2',
detail_id VARCHAR(50) '#id',
detail_1 VARCHAR(50),
detail_2 VARCHAR(50)
)
EXEC sp_xml_removedocument #iDoc
CREATE INDEX #IX_temp ON #temp(match_field_1, match_field_2)
CREATE INDEX #IX_detail ON #detail(match_field_1, match_field_2, detail_id)
MERGE data_table a
USING #temp ta
ON ta.match_field_1 = a.match_field_1 AND ta.match_field_2 = a.match_field_2
WHEN MATCHED THEN
UPDATE SET data_1 = ta.data_1, data_2 = ta.data_2
WHEN NOT MATCHED THEN
INSERT (match_field_1, match_field_2, data_1, data_2) VALUES (ta.match_field_1, ta.match_field_2, ta.data_1, ta.data_2)
MERGE detail_table a
USING (SELECT d.*, p._key FROM #detail d, data_table p WHERE d.match_field_1 = p.match_field_1 AND d.match_field_2 = p.match_field_2) ta
ON a.id = ta.id AND a.parent_key = ta._key
WHEN MATCHED THEN
UPDATE SET detail_1 = ta.detail_1, detail2 = ta.detail_2
WHEN NOT MATCHED THEN
INSERT (parent_key, id, detail_1, detail_2) VALUES (ta._key, ta.id, ta.detail_1, ta.detail_2)
DROP TABLE #temp
DROP TABLE #detail
END
Use (3). Process the data ready for upset in C#. C# is made for this kind of algorithmic work. It is both the right programming language as well as the faster programming language. T-SQL is not the right tool. You do not want to use XML with T-SQL for very high performance stuff because it burns CPU like crazy. Instead use the fast TDS protocol to send TVP or bulk data.
Then, send the data to the server using either a TVP or a bulk-insert (SqlBulkCopy) to a temp table. The latter technique is great for very many rows (>10k?). Bulk insert uses special TDS features. It does not use SQL batches to transfer the data. It does not get faster than this.
Then use the MERGE statement as you described. Use big batch sizes, potentially all rows in one batch.
The best way I've found is to bulk insert into a temp table from your C# code, then issue the merge once the data is in SQL Server. I have an example here on my blog SQL Server Bulk Upsert
I use this in production to insert millions of rows daily, and have yet to find a faster way to do it. Give it a try, I think you will be impressed with the performance of the solution.
I have one problem in which i simply want to know how i can create a table that can easily Used as a back end for my solution that is in Vb 2010.
I also want to know that when we choose a data source in a vb.net that is for sql server Which we want to choose....simply which can be used Because there is 2 or 3 with little different name.....
I'm struggling to understand your question, but in an effort to help:
I'm guessing that you want to programmatically create a table to be used by other parts of your VB application, but that you need to ensure the table name is unique...? If I'm right in that assumption, then see below.
You can use this query:
SELECT *
FROM INFORMATION_SCHEMA.TABLES
WHERE table_type = 'BASE TABLE'
To get a list of table names currently in your database. You can compare the TABLE_NAME column values with your desired table name. If it exists already, change the name by adding an differentiator, eg: MyTable, MyTable1, MyTable2 etc.
Alternatively, SQL Server accepts Guids as table names.
Disclaimer: IMHO, If your table is not going to be temporary deciding table names in this manner is a pretty ugly solution and lacks supportability.
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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