I have a table of about 800 000 records. Its basically a log which I query often.
I gave condition to query only queries that were entered last month in attempt to reduce the load on a database.
My thinking is
a) if the database goes only through the first month and then returns entries, its good.
b) if the database goes through the whole database + checking the condition against every single record, it's actually worse than no condition.
What is your opinion?
How would you go about reducing load on a dbf?
If the field containing the entry date is keyed/indexed, and is used by the DB software to optimize the query, that should reduce the set of rows examined to the rows matching that date range.
That said, it's a commonly understood that you are better off optimizing queries, indexes, database server settings and hardware, in that order. Changing how you query your data can reduce the impact of a query a millionfold for a query that is badly formulated in the first place, depending on the dataset.
If there are no obvious areas for speedup in how the query itself is formulated (joins done correctly or no joins needed, or effective use of indexes), adding indexes to help your common queries would by a good next step.
If you want more information about how the database is going to execute your query; you can use the MySQL EXPLAIN command to find out. For example, that will tell you if it's able to use an index for the query.
Related
So i have database in project Mysql .
I have a main table that have main staff for updating and inserting .
I have huge data traffic on the data . what i am doing mainly reading .csv file and inserting to table .
Everything works file for 3 days but when table record goes above 20 million the database start responding slow , and in 60 million more slow.
What i have done ?
I have applied index in the record where i think i need of it . (where clause field for fast searching) .
I think query optimisation can not be issue because database working fine for 3 days and when data filled in table it get slow . and as i reach 60 million it work more slow .
Can you provide me the approach how can i handle this ?
What should i do ? Should i shift data in every 3 days or what ? What you have done in such situation .
The purpose of database is to store a huge information. I think the problem is not in your database, it should be poor query, joins, Database buffer, index and cache. These are the following reason which makes your response to slow up. For more info check this link
I have applied index in the record where i think i need of it
Yes, index improve the performance of SELECT query, but at the same time it will degrade your DML operation and index has to be restructure whenever you perform any changes to indexed column.
Now, this is totally depending on your business need, whether you need index or not, whether you can compromise SELECT or DML.
Currently, many industries uses two different schemas OLAP for reporting and analytics and OLTP to store real-time data (including some real-time reporting).
First of all it could be helpful for us to now which kind of data you want to store.
Normally it makes no sense to store such a huge amount of data in 3 days because no one ever will be able to use this in an effective way. So it is better to reduce the data before storing in the database.
e.g.
If you get measuring values from a device which gives you one value a millisecond, you should think if any user is ever asking for a special value at a special millisecond or if it not makes more sense to calculate the average value of once a second, minute or hour or perhaps once a day?
If you really need the milliseconds but only if the user takes a deeper look, you can create a table from the main table with only the average values of an hour or day or whatever and work with that table. Only if the user goes in ths "milliseconds" view you use the main table and have to live with the more bad performance.
This all is of course only possible if the database data is read only. If the data in the database is changed from the application (and not only appended by the CSV import) then using more then one table will be error prone.
Whick operation do you want to speed up?
insert operation
A good way to speed it up is to insert records in batch. For example, insert 1000 records in each insert statement:
insert into test values (value_list),(value_list)...(value_list);
other operations
If your table got tens of millions of records, everything will be slowing down. This is quite common.
To speed it up in this situation, here is some advice:
Optimize your table definition. It depends on your particular case. Creating indexes is a common way.
Optimize your SQL statements. Apparently a good SQL statement will run much faster, and a bad SQL statement might be a performance killer.
Data migration. If only part of your data is used frequently, you can shift the infrequently-used data to another big table.
Sharding. This is a more complicated way, but usually used in big data system.
For the .csv file, use LOAD DATA INFILE ...
Are you using InnoDB? How much RAM do you have? What is the value of innodb_buffer_pool_size? That may not be set right -- based on queries slowing down as the data increases.
Let's see a slow query. And SHOW CREATE TABLE. Often a 'composite' index is needed. Or reformulation of the SELECT.
I have a problem with my MySQL database. I got an expensive query with some joins. But i run it always for one specific id, which makes the execution very fast.
Now, i put this query into a view. If i query this view and use the where clause with the id on the view, it seems as if MySQL at first loads all records and after that applies my where clause. This results in a very bad performance.
Is there a possibility to let MySQL use also my where clauses in the view before querying all records?
Thanks a lot and cheers,
Argonitas
I have a query that is running very slowly. The table is was querying has about 100k records and no indexes on most of the columns used in the where clause. I just added indexes on those columns but the query hasn't gotten any faster.
I think this is because when a column is indexed, it's value is written in the index at the time of insertion. I just added the indexes now after all those records were added. So is there a way to "re-run the indexes" on the table?
Edit
Here is the query and explain result:
Oddly enough when I copy the query and run in directly in my SQL manager tool it runs quite fast so may bye the problem is in my application code and not in the query itself.
Mysql keeps consistent indexes. It does not matter if the data is added first, the index is added first, or the data is changed at any time. The same final index will result (assuming the same final data and index type).
Your slow query is not caused by adding the index later. There will be some other reason.
This is an extremely common problem.
Use MySQL explain http://dev.mysql.com/doc/refman/5.0/en/using-explain.html
When you precede a SELECT statement with the keyword EXPLAIN, MySQL displays information from the optimizer about the query execution plan. That is, MySQL explains how it would process the statement, including information about how tables are joined and in which order.
Using these results... verify the index you created is functioning the way you expected.
If not, you will want to tweak your index until you have it working as expected.
You might want to create a new table, create indexes, then insert all elements from old table to new while testing this. It's easier than dropping and re-adding indices a million times.
I have two tables TABLE A and TABLE B.
TABLE A contain 1 million (1,000,000) records and 4 fields while TABLE 2 contain 60,000 and 3 fields.
I am running a query which joins these two tables and usees WHERE clause to find specific products like WHERE product like '%Bags%' and product like 'Bags%' e.t.c.
When I run the query directly in phpMyAdmin then it returns records in around 1 or 2 seconds. But when they are being used on website, they are sometime taking 9 or 10 seconds according to MySQL 'slow query' log. Actually my website response was very slow at times so upon investigation I found out it is due to MySQL as I came to know about 'slow query log'.
The slow query log consists of all SQL statements that took more than long_query_time seconds to execute and required at least min_examined_row_limit rows to be examined.
So according to that log "query_time" for above query was 13 seconds while in some cases they even had "query_time" exceeding 50 seconds.
Both my tables are using PRIMARY keys as well as INDEXES. So I want to know how can I optimize them more or is there any way I can optimize MySQL settings in general?
This slowness of website doesn't happen all the time but sometimes (may be once in a week) and lasts for around 1 or 2 minutes. It gets decent amount of traffic and there are many other queries too, the above I posted was just one example.
Thanks
For all things MySQL and performance related, check out http://www.mysqlperformanceblog.com/
Check your queries with EXPLAIN, see here and here for info on how to use EXPLAIN as query diagnostic tool.
It's not enough to just have indexes. Are you indexing the fields searched in the WHERE clause? Also do you have indexes for the fields used in the WHERE clause (including the fields you mention in ORDER BY, GROUP BY, and HAVING clauses as well as JOINs)? If you have grouped fields in a single index, that index won't be hit unless you have a query that searches all those fields together. If you group fields in an index make sure they the index will actually be used in your query (EXPLAIN is your friend).
That said, it could be many other things as well: poorly configured MySQL server, poorly tuned server, bad schema. But your queries and your indexes are good place to start your investigation.
Here is a nice summary of performance best practices from Jay Pipes of MySQL.
like '%Bags%' query cannot be optimized using indexes.
The only way to improve performance here is to use fulltext indexes or get sphinx to search.
Its because of some other queries are run at the time when you are going to refresh the page of your website. so if for example your website going to run 8-10 queries at time of page refresh then it will take some more time than you run single query in phpmyadmin. and if its take 1-1.5 min to execute then its may not the query problem but it may have prob with the server speed also.
and you also can use MATCH() AGAINST() statement for optimize this type of search queries.
Otherwise you are already using PRIMARY KEY, INDEXES and JOINS so there is no need to worry about other things.
just check it out.
Thanks.
There are many ways to optimize Databases and queries. My method is the following.
Look at the DB Schema and see if it makes sense
Most often, Databases have bad designs and are not normalized. This can greatly affect the speed of your Database. As a general case, learn the 3 Normal Forms and apply them at all times. The normal forms above 3rd Normal Form are often called de-normalization forms but what this really means is that they break some rules to make the Database faster.
What I suggest is to stick to the 3rd normal form except if you are a DBA (which means you know subsequent forms and know what you're doing). Normalization after the 3rd NF is often done at a later time, not during design.
Only query what you really need
Filter as much as possible
Your Where Clause is the most important part for optimization.
Select only the fields you need
Never use "Select *" -- Specify only the fields you need; it will be faster and will use less bandwidth.
Be careful with joins
Joins are expensive in terms of time. Make sure that you use all the keys that relate the two tables together and don't join to unused tables -- always try to join on indexed fields. The join type is important as well (INNER, OUTER,... ).
Optimize queries and stored procedures (Most Run First)
Queries are very fast. Generally, you can retrieve many records in less than a second, even with joins, sorting and calculations. As a rule of thumb, if your query is longer than a second, you can probably optimize it.
Start with the Queries that are most often used as well as the Queries that take the most time to execute.
Add, remove or modify indexes
If your query does Full Table Scans, indexes and proper filtering can solve what is normally a very time-consuming process. All primary keys need indexes because they makes joins faster. This also means that all tables need a primary key. You can also add indexes on fields you often use for filtering in the Where Clauses.
You especially want to use Indexes on Integers, Booleans, and Numbers. On the other hand, you probably don't want to use indexes on Blobs, VarChars and Long Strings.
Be careful with adding indexes because they need to be maintained by the database. If you do many updates on that field, maintaining indexes might take more time than it saves.
In the Internet world, read-only tables are very common. When a table is read-only, you can add indexes with less negative impact because indexes don't need to be maintained (or only rarely need maintenance).
Move Queries to Stored Procedures (SP)
Stored Procedures are usually better and faster than queries for the following reasons:
Stored Procedures are compiled (SQL Code is not), making them faster than SQL code.
SPs don't use as much bandwidth because you can do many queries in one SP. SPs also stay on the server until the final results are returned.
Stored Procedures are run on the server, which is typically faster.
Calculations in code (VB, Java, C++, ...) are not as fast as SP in most cases.
It keeps your DB access code separate from your presentation layer, which makes it easier to maintain (3 tiers model).
Remove unneeded Views
Views are a special type of Query -- they are not tables. They are logical and not physical so every time you run select * from MyView, you run the query that makes the view and your query on the view.
If you always need the same information, views could be good.
If you have to filter the View, it's like running a query on a query -- it's slower.
Tune DB settings
You can tune the DB in many ways. Update statistics used by the optimizer, run optimization options, make the DB read-only, etc... That takes a broader knowledge of the DB you work with and is mostly done by the DBA.
****> Using Query Analysers****
In many Databases, there is a tool for running and optimizing queries. SQL Server has a tool called the Query Analyser, which is very useful for optimizing. You can write queries, execute them and, more importantly, see the execution plan. You use the execution to understand what SQL Server does with your query.
Actually i queried optimize table query for one table. then i didn't do any operation on that table. then again i'm querying optimize table query at the end of every month. but the data in the table may be changed once in four or 8 months. is it create any problem in performance of the mysql query?
If you don't do DML operations on the table, OPTIMIZE TABLE is useless.
OPTIMIZE TABLE cleans the table of deleted records, sorts the index pages (brings the physical order of the pages in consistence to logical one) and recalculates the statistics.
For the duration of the command, the table is unavailable both for reading and writing, and the command may take long for large tables.
Did your read the manual about OPTIMIZE? And do you have a problem you want to solve using OPTIMIZE? If not, don't use this statement at all.
If the data doesn't quite change over a period of 4-8 months it should not create any issue with performance for the end of month report.
However if the count of rows that are changed in the 4-8 months period is huge then you would want to rebuild indexes/analyze the tables so that the queries run fine after the load.