I have an Aurora MySQL cluster and when running queries against the reader I see a degradation in performance over time. A reboot of the reader results in query performance that matches the writer. But after going a week without a reboot queries take 25x as long to run.
The replication lag for the reader instance is 20ms and none of the monitoring metrics are showing issues. The highest I have seen the CPU is 40%. I tried a suggestion to set block_nested_loop to off but that had no effect.
The reader does not get much activity so load should not be an issue. We do need to run a complex query against it that returns a lot of data which is used for analytics. I have found that queries that return a small number of records that are retrieved by an index do NOT have the performance problem. But a similar query that returns the same small number of records and requires a table scan does have the performance problem.
The rate of degradation seems consistent, so it seems like a resource issue related to replication, but I have not had any luck finding anything online documenting the issue.
Any help would be much appreciated.
Update: Additional details
Query execution plans
-- Fast query
explain select cpv.SHORT_TEXT_VALUE, c.UIDPK, c.GUID, c.SHARED_ID, cpv.*
from TCUSTOMERPROFILEVALUE cpv
inner join TCUSTOMER c on cpv.CUSTOMER_UID = c.UIDPK
where LOCALIZED_ATTRIBUTE_KEY = 'CP_EMAIL' and cpv.SHORT_TEXT_VALUE = 'some-email#gmail.com';
-- Slow query, using function to prevent use of index for email match
explain select cpv.SHORT_TEXT_VALUE, c.UIDPK, c.GUID, c.SHARED_ID, cpv.*
from TCUSTOMERPROFILEVALUE cpv
inner join TCUSTOMER c on cpv.CUSTOMER_UID = c.UIDPK
where LOCALIZED_ATTRIBUTE_KEY = 'CP_EMAIL' and LOWER(cpv.SHORT_TEXT_VALUE) = 'some-email#gmail.com';
Table definitions
CREATE TABLE `TCUSTOMERPROFILEVALUE` (
`UIDPK` bigint(20) NOT NULL,
`ATTRIBUTE_UID` bigint(20) NOT NULL,
`ATTRIBUTE_TYPE` int(11) NOT NULL,
`LOCALIZED_ATTRIBUTE_KEY` varchar(255) NOT NULL,
`SHORT_TEXT_VALUE` varchar(255) DEFAULT NULL,
`LONG_TEXT_VALUE` mediumtext,
`INTEGER_VALUE` int(11) DEFAULT NULL,
`DECIMAL_VALUE` decimal(19,2) DEFAULT NULL,
`BOOLEAN_VALUE` int(11) DEFAULT '0',
`DATE_VALUE` datetime DEFAULT NULL,
`CUSTOMER_UID` bigint(20) DEFAULT NULL,
`LAST_MODIFIED_DATE` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
`CREATION_DATE` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (`UIDPK`),
KEY `I_CPV_ATTR_UID` (`ATTRIBUTE_UID`),
KEY `I_CPV_CUID_ATTKEY` (`CUSTOMER_UID`,`LOCALIZED_ATTRIBUTE_KEY`),
KEY `I_CPV_STV_ATTVALUE` (`SHORT_TEXT_VALUE`),
KEY `I_CPV_ATTKEY_SHORTTEXT` (`LOCALIZED_ATTRIBUTE_KEY`,`SHORT_TEXT_VALUE`),
CONSTRAINT `FK_PROFILE_CUSTOMER` FOREIGN KEY (`CUSTOMER_UID`) REFERENCES `TCUSTOMER` (`UIDPK`) ON DELETE CASCADE,
CONSTRAINT `TCUSTOMERPROFILEVALUE_FK_1` FOREIGN KEY (`ATTRIBUTE_UID`) REFERENCES `TATTRIBUTE` (`UIDPK`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='values associated with customer profiles.'
CREATE TABLE `TCUSTOMER` (
`UIDPK` bigint(20) NOT NULL,
`PREF_BILL_ADDRESS_UID` bigint(20) DEFAULT NULL,
`PREF_SHIP_ADDRESS_UID` bigint(20) DEFAULT NULL,
`CREATION_DATE` datetime NOT NULL,
`LAST_EDIT_DATE` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
`GUID` varchar(64) NOT NULL,
`STATUS` int(11) NOT NULL,
`AUTHENTICATION_UID` bigint(20) DEFAULT NULL,
`STORECODE` varchar(64) DEFAULT NULL,
`IS_FIRST_TIME_BUYER` tinyint(4) DEFAULT '1',
`CUSTOMER_TYPE` varchar(64) NOT NULL,
`SHARED_ID` varchar(255) NOT NULL,
`PARENT_CUSTOMER_GUID` varchar(64) DEFAULT NULL,
`DTYPE` varchar(40) DEFAULT 'ExtCustomerImpl',
`LAST_SESSION_DATE` timestamp NULL DEFAULT NULL,
PRIMARY KEY (`UIDPK`),
UNIQUE KEY `TCUSTOMER_UNIQUE` (`GUID`),
UNIQUE KEY `TCUSTOMER_SHARED_ID_TYPE_UNIQ` (`SHARED_ID`,`CUSTOMER_TYPE`),
UNIQUE KEY `I_CUST_AUTH_UID` (`AUTHENTICATION_UID`),
UNIQUE KEY `SHARED_ID` (`SHARED_ID`,`STORECODE`),
KEY `I_CUST_CR_DATE` (`CREATION_DATE`),
KEY `I_CUST_STORE_CODE` (`STORECODE`),
KEY `I_TYPE_LAST_EDIT` (`CUSTOMER_TYPE`,`LAST_EDIT_DATE`),
KEY `I_CUSTOMER_SHAREDID` (`SHARED_ID`),
KEY `I_CUSTOMER_PARENT` (`PARENT_CUSTOMER_GUID`),
CONSTRAINT `CUSTOMER_STORECODE_FK` FOREIGN KEY (`STORECODE`) REFERENCES `TSTORE` (`STORECODE`),
CONSTRAINT `TCUSTOMER_PARENT_GUID_FK` FOREIGN KEY (`PARENT_CUSTOMER_GUID`) REFERENCES `TCUSTOMER` (`GUID`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='customer account information.'
Indexes
Well, I can't explain the shift in performance unless the Optimizer is randomly shifting between different query plans.
I do see that you are using the notorious Entity-Attribute-Value schema design. And doing it in a rather bulky and complex way -- with multiple columns for different datatypes.
I do see a few things that can probably help performance in general as the dataset grows. (I assume it will grow.)
The primary key, UIDPK of the attribute table TCUSTOMERPROFILEVALUE probably has no use. This will probably be better: PRIMARY KEY(CUSTOMER_UID, ATTRIBUTE_UID). Or maybe that should be LOCALIZED_ATTRIBUTE_KEY??? Why are there two columns for the attribute?
When changing the PK, this KEY I_CPV_ATTKEY_SHORTTEXT (LOCALIZED_ATTRIBUTE_KEY,SHORT_TEXT_VALUE) would implicitly have CUSTOMER_UID added on the end, thereby benefiting your JOIN.
BIGINT is usually overkill; consider using a smaller datatype.
Do you have another attribute table - TATTRIBUTE?
Having 5 UNIQUE keys for a table slows down inserts. Perhaps you can have fewer?
INDEX(SHARED_ID) is redundant since there are other keys starting with that column.
Have your tried removing the LOWER(xxxx) from the SLOW QUERY?
If this corrects the problem, and your results are the same, you were just wasting time with the LOWER(xxx) manipulation.
Related
I am using mysql with Django. I am trying to count the number of visitor_pages for a specific dealer in a certain amount of time.
I would share the raw sql query that I have obtained from django debug toolbar.
SELECT COUNT(*) AS `__count`
FROM `visitor_page`
INNER JOIN `dealer_visitors`
ON (`visitor_page`.`dealer_visitor_id` = `dealer_visitors`.`id`)
WHERE (`visitor_page`.`date_time` BETWEEN '2021-02-01 05:51:00'
AND '2021-03-21 05:50:00'
AND `dealer_visitors`.`dealer_id` = 15)
The issue is that I have more than 13 million records in the visitor_pages table and about 1.5 million records in the dealer_visitor table. I have already indexed date_time. I am thinking of using a materialized view but before attempting that, I would really appreciate suggestions on how I could improve this query.
visitor_pages schema:
CREATE TABLE `visitor_page` (
`id` int NOT NULL AUTO_INCREMENT,
`date_time` datetime(6) DEFAULT NULL,
`added_at` datetime(6) DEFAULT NULL,
`updated_at` datetime(6) DEFAULT NULL,
`page_id` int NOT NULL,
`dealer_visitor_id` int NOT NULL,
PRIMARY KEY (`id`),
KEY `visitor_page_page_id_246babdf_fk_web_page_id` (`page_id`),
KEY `visitor_page_dealer_visitor_id_e2dddea2_fk_dealer_visitors_id` (`dealer_visitor_id`),
KEY `visitor_page_date_time_06e9e9f5` (`date_time`),
CONSTRAINT `visitor_page_dealer_visitor_id_e2dddea2_fk_dealer_visitors_id` FOREIGN KEY (`dealer_visitor_id`) REFERENCES `dealer_visitors` (`id`),
CONSTRAINT `visitor_page_page_id_246babdf_fk_web_page_id` FOREIGN KEY (`page_id`) REFERENCES `web_page` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=13626649 DEFAULT CHARSET=latin1;
dealer_visitors schema:
CREATE TABLE `dealer_visitors` (
`id` int NOT NULL AUTO_INCREMENT,
`visit_date` datetime(6) DEFAULT NULL,
`added_at` datetime(6) DEFAULT NULL,
`updated_at` datetime(6) DEFAULT NULL,
`dealer_id` int NOT NULL,
`visitor_id` int NOT NULL,
`type` int DEFAULT NULL,
`notes` longtext,
`location` varchar(100) DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `dealer_visitors_dealer_id_306e2202_fk_dealer_id` (`dealer_id`),
KEY `dealer_visitors_visitor_id_27ae498e_fk_visitor_id` (`visitor_id`),
KEY `dealer_visitors_type_af0f7d79` (`type`),
KEY `dealer_visitors_visit_date_f2b138c9` (`visit_date`),
CONSTRAINT `dealer_visitors_dealer_id_306e2202_fk_dealer_id` FOREIGN KEY (`dealer_id`) REFERENCES `dealer` (`id`),
CONSTRAINT `dealer_visitors_visitor_id_27ae498e_fk_visitor_id` FOREIGN KEY (`visitor_id`) REFERENCES `visitor` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=1524478 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
EXPLAIN ANALYZE the query gives me the following:
EXPLAIN:
For this query:
SELECT COUNT(*) AS `__count`
FROM visitor_page vp JOIN
dealer_visitors dv
ON vp.dealer_visitor_id = dv.id
WHERE vp.date_time BETWEEN '2021-02-01 05:51:00' AND '2021-03-21 05:50:00' AND
dv.dealer_id = 15;
The best indexes are on dealer_visitors(dealer_id, date_time, id) and visitor_page(dealer_visitor_id).
An index only on date helps a bit. But you are retrieving a month's worth of data and that might be a lot of data to process. Having dealer_id as the first column in the index will restrict the data to only the rows for that dealer in that time frame.
Depending on the distribution of the data, the Optimizer might pick one of the tables to start with, or pick the other. So, let's provide optimal indexes for each case:
ON `visitor_page`.`dealer_visitor_id` = `dealer_visitors`.`id`
WHERE `visitor_page`.`date_time` BETWEEN ...
AND `dealer_visitors`.`dealer_id` = 15
Starting with visitor_page:
visitor_page: INDEX(date_time) -- (already exists)
dealer_visitors: (already has PRIMARY KEY(id))
Starting with dealer_visitors:
dealer_visitors: INDEX(dealer_id) -- (already exists)
visitor_page: INDEX(dealer_visitor_id, date_time) -- in this order
and drop dealer_visitors_visitor_id_27ae498e_fk_visitor_id as now being redundant.
The net is to add one index and drop one index.
Materialized view -- It is often best for Data Warehouse reports to build and incrementally maintain a "summary table" (a "materialized view"). The very odd date range (1 month + 20 days - 61 seconds) makes this clumsy to do. Typically it is handy to make the table based on whole days. If you can shift to daily (or hourly), then see http://mysql.rjweb.org/doc.php/summarytables
Something else to check: How much RAM do you have? What does SHOW VARIABLES LIKE 'innodb_buffer_pool_size'; say?
I see that the tables have different charset/collation. This is not a problem for the query in question, but if you have other queries that JOIN on VARCHARs, check that they use the same collation.
I have a MySQL database table with more than 34M rows (and growing).
CREATE TABLE `sensordata` (
`userID` varchar(45) DEFAULT NULL,
`instrumentID` varchar(10) DEFAULT NULL,
`utcDateTime` datetime DEFAULT NULL,
`dateTime` datetime DEFAULT NULL,
`data` varchar(200) DEFAULT NULL,
`dataState` varchar(45) NOT NULL DEFAULT 'Original',
`gps` varchar(45) DEFAULT NULL,
`location` varchar(45) DEFAULT NULL,
`speed` varchar(20) NOT NULL DEFAULT '0',
`unitID` varchar(5) NOT NULL DEFAULT '1',
`parameterID` varchar(5) NOT NULL DEFAULT '1',
`originalData` varchar(200) DEFAULT NULL,
`comments` varchar(45) DEFAULT NULL,
`channelHashcode` varchar(12) DEFAULT NULL,
`settingHashcode` varchar(12) DEFAULT NULL,
`status` varchar(7) DEFAULT 'Offline',
`id` int(11) NOT NULL AUTO_INCREMENT,
PRIMARY KEY (`id`),
UNIQUE KEY `id_UNIQUE` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=98772 DEFAULT CHARSET=utf8
I access this table from multiple threads (at least 400 threads) every minute to insert data into the table.
As the table was growing, it was getting slower to read and write the data. One SELECT query used to take about 25 seconds, then I added a unique index
UNIQUE INDEX idx_userInsDate ( userID,instrumentID,utcDateTime)
This reduced the read time from 25 seconds to some milliseconds but it has increased the insert time as it has to update the index for each record.
Also If I run a SELECT query from multiple threads as the same time the queries take too long to return the data.
This is an example query
Select dateTime from sensordata WHERE userID = 'someUserID' AND instrumentID = 'someInstrumentID' AND dateTime between 'startDate' AND 'endDate' order by dateTime asc;
Can someone help me, to improve the table schema or add an effective index to improve the performance, please.
Thank you in advance
A PRIMARY KEY is a UNIQUE key. Toss the redundant UNIQUE(id) !
Is id referenced by any other tables? If not, then get rid of it all together. Instead have just
PRIMARY KEY ( userID, instrumentID, utcDateTime)
That is, if that triple is guaranteed to be unique. You mentioned DST -- use the datatype TIMESTAMP instead of DATETIME. Doing that, you can convert to DATETIME if needed, thereby eliminating one of the columns.
That one index (the PK) takes virtually no space since it is "clustered" with the data in InnoDB.
Your table is awfully fat with all those VARCHARs. For example, status can be reduced to a 1-byte ENUM. Others can be normalized. Things like speed can be either a 4-byte FLOAT or some smaller DECIMAL, depending on how much range and precision you need.
With 34M wide rows, you have probably recently exceeded the cacheability of the RAM you have. By making the row narrower, you will postpone that overflow.
Why attack the indexes? Every UNIQUE (including PRIMARY) index is checked before allowing the row to be inserted. By getting it down to 1 index, that minimizes the cost there. (InnoDB really needs a PRIMARY KEY.)
INT is 4 bytes. Do you have a billion instruments? Maybe instrumentID could be SMALLINT UNSIGNED, which is 2 bytes, with a max of 64K? Think about all the other IDs.
You have 400 INSERTs/minute, correct? That is not bad. If you get to 400/second, we need to have a different talk.
("Fill factor" is not tunable in MySQL because it does not make much difference.)
How much RAM do you have? What is the setting for innodb_buffer_pool_size? Optimal is somewhere around 70% of available RAM.
Let's see your main queries; there may be other issues to address.
It's not the indexes at fault here. It's your data types. As the size of the data on disk grows, the speed of all operations decrease. Indexes can certainly help speed up selects - provided your data is properly structured - but it appears that it isnt
CREATE TABLE `sensordata` (
`userID` int, /* shouldn't this have a foreign key constraint? */
`instrumentID` int,
`utcDateTime` datetime DEFAULT NULL,
`dateTime` datetime DEFAULT NULL,
/* what exactly are you putting here? Are you sure it's not causing any reduncy? */
`data` varchar(200) DEFAULT NULL,
/* your states will be a finite number of elements. They can be represented by constants in your code or a set of values in a related table */
`dataState` int,
/* what's this? Sounds like what you are saving in location */
`gps` varchar(45) DEFAULT NULL,
`location` point,
`speed` float,
`unitID` int DEFAULT '1',
/* as above */
`parameterID` int NOT NULL DEFAULT '1',
/* are you sure this is different from data? */
`originalData` varchar(200) DEFAULT NULL,
`comments` varchar(45) DEFAULT NULL,
`channelHashcode` varchar(12) DEFAULT NULL,
`settingHashcode` varchar(12) DEFAULT NULL,
/* as above and isn't this the same as */
`status` int,
`id` int(11) NOT NULL AUTO_INCREMENT,
PRIMARY KEY (`id`),
UNIQUE KEY `id_UNIQUE` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=98772 DEFAULT CHARSET=utf8
1st of all: Avoid varchars for indexes and especially IDs. Each character position in the varchar generates an own index-entry internally!
2nd: Your select uses dateTime, your index is set to utcDateTime. It will only take userID and instrumentID and ignore the utcDateTime-Part.
Advise: Change your data types for the ids and change your index to match the query (dateTime, not utcDateTime)
Using an index decreases your performance on inserts, unluckily, there is nothing such as a fill factor for indexes in mysql right now. So the best thing you can do is try the indexes to be as small as possible.
Another approach on heavily loaded databases with random access would be: write to an unindexed table, read from an indexed one. At a given time, build the indexes and swap the tables (may require a third table for the index creation while leaving the other ones untouched in between).
I am using a MySQL database in my ASP.NET with C# web application. The MySQL Server version is 5.7 and there is 8 GB RAM in the PC. When I am executing the select query in MySQL database table, it takes more time in execution; a simple select query takes around 42 seconds. Across 1 crorerecord (10 million records) in the table. I have also done indexing for the table. How can I fix this?
The following is my table structure.
CREATE TABLE `smstable_read` (
`MessageID` int(11) NOT NULL AUTO_INCREMENT,
`ApplicationID` int(11) DEFAULT NULL,
`Api_userid` int(11) DEFAULT NULL,
`ReturnMessageID` varchar(255) DEFAULT NULL,
`Sequence_Id` int(11) DEFAULT NULL,
`messagetext` longtext,
`adtextid` int(11) DEFAULT NULL,
`mobileno` varchar(255) DEFAULT NULL,
`deliverystatus` int(11) DEFAULT NULL,
`SMSlength` int(11) DEFAULT NULL,
`DOC` varchar(255) DEFAULT NULL,
`DOM` varchar(255) DEFAULT NULL,
`BatchID` int(11) DEFAULT NULL,
`StudentID` int(11) DEFAULT NULL,
`SMSSentTime` varchar(255) DEFAULT NULL,
`SMSDeliveredTime` varchar(255) DEFAULT NULL,
`SMSDeliveredTimeTicks` decimal(28,0) DEFAULT '0',
`SMSSentTimeTicks` decimal(28,0) DEFAULT '0',
`Sent_SMS_Day` int(11) DEFAULT NULL,
`Sent_SMS_Month` int(11) DEFAULT NULL,
`Sent_SMS_Year` int(11) DEFAULT NULL,
`smssent` int(11) DEFAULT '1',
`Batch_Name` varchar(255) DEFAULT NULL,
`User_ID` varchar(255) DEFAULT NULL,
`Year_ID` int(11) DEFAULT NULL,
`Date_Time` varchar(255) DEFAULT NULL,
`IsGroup` double DEFAULT NULL,
`Date_Time_Ticks` decimal(28,0) DEFAULT NULL,
`IsNotificationSent` int(11) DEFAULT NULL,
`Module_Id` double DEFAULT NULL,
`Doc_Batch` decimal(28,0) DEFAULT NULL,
`SMS_Category_ID` int(11) DEFAULT NULL,
`SID` int(11) DEFAULT NULL,
PRIMARY KEY (`MessageID`),
KEY `index2` (`ReturnMessageID`),
KEY `index3` (`mobileno`),
KEY `BatchID` (`BatchID`),
KEY `smssent` (`smssent`),
KEY `deliverystatus` (`deliverystatus`),
KEY `day` (`Sent_SMS_Day`),
KEY `month` (`Sent_SMS_Month`),
KEY `year` (`Sent_SMS_Year`),
KEY `index4` (`ApplicationID`,`SMSSentTimeTicks`),
KEY `smslength` (`SMSlength`),
KEY `studid` (`StudentID`),
KEY `batchid_studid` (`BatchID`,`StudentID`),
KEY `User_ID` (`User_ID`),
KEY `Year_Id` (`Year_ID`),
KEY `IsNotificationSent` (`IsNotificationSent`),
KEY `isgroup` (`IsGroup`),
KEY `SID` (`SID`),
KEY `SMS_Category_ID` (`SMS_Category_ID`),
KEY `SMSSentTimeTicks` (`SMSSentTimeTicks`)
) ENGINE=MyISAM AUTO_INCREMENT=16513292 DEFAULT CHARSET=utf8;
The following is my select query:
SELECT messagetext, SMSSentTime, StudentID, batchid,
User_ID,MessageID,Sent_SMS_Day, Sent_SMS_Month,
Sent_SMS_Year,Module_Id,Year_ID,Doc_Batch
FROM smstable_read
WHERE StudentID=977 AND SID = 8582 AND MessageID>16013282
You need to learn about compound indexes and covering indexes. Read about those things.
Your query is slow because it's doing a half-scan of the table. It uses the primary key to find the first row with a qualifying MessageID, then looks at every row of the table to find matching rows.
Your filter criteria are StudentID = constant, SID = constant AND MessageID > constant. That means you need those three columns, in that order, in an index. The first two filter criteria will random-access your index to the correct place. The third criterion will scan the index starting right after the constant value in your query. It's called an Index Range Scan operation, and it's quite efficient.
ALTER TABLE smstable_read
ADD INDEX StudentSidMessage (StudentId, SID, MessageId);
This compound index should make your query efficient. Notice that in MyISAM, the primary key column of a table should appear in compound indexes. That's cool in this case because it's also part of your query criteria.
If this query is used very frequently, you could make a covering index: you could add the other columns of the query (the ones mentioned in your SELECT clause) to the index.
But, unfortunately you have defined your messageText column with a longtext data type. That allows for each message to contain up to four gigabytes. (Why? Is this really SMS data? There's a limit of 160 bytes per message in SMS. Four gigabytes >> 160 bytes.)
Now the point of a covering index is to allow the query to be satisfied entirely from the index, without referring back to the table. But when you include a longtext or any other LOB column in an index, it only contains a subset of the data. So the point of the covering index is lost.
If I were you I would change my table so messageText was a VARCHAR(255) data type, and then create this covering index:
ALTER TABLE smstable_read
ADD INDEX StudentSidMessage (StudentId, SID, MessageId,
SMSSentTime, batchid,
User_ID, Sent_SMS_Day, Sent_SMS_Month,
Sent_SMS_Year,Module_Id,Year_ID,Doc_Batch,
messageText);
(Notice that you should put variable-length items last in the index if you can.)
If you can't change your application to handle VARCHAR(255) then go with the first index I mentioned.
Pro tip: putting lots of single-column indexes on MySQL tables rarely helps SELECT performance and always harms INSERT and UPDATE performance. You need an index on your primary key, and you need indexes to support the queries you run. Extra indexes are harmful.
It looks like your database is not properly indexed and even not properly normalized. Normalizing your database will go a long way to speed up all your queries. Particularly in view of the fact that mysql used only one index per table in a query. Even though you have lot's of indexes, they cannot be used.
Your current query filters on StudentID,SID, and MessageID. The last is an inequality comparision so an index will not be very effective with that but the other two columns are equality comparisons. I suggest an index like this:
KEY `studid` (`StudentID`,`SID`)
Follow that up by dropping your existing index on SID. If you find that you don't want to drop it because it's used in another query, further evidence that your table is in desperate need of normalization.
Too many indexes slow down inserts and adds a little overhead to each SELECT because the query planner needs more effort to figure out which index to use.
I have a large live database where around 1000 users are updating 2 or more updates every minute. at the same time there are 4 users are getting reports and adding new items. the main 2 tables contains around 2 Million and 4 Million rows till present.
Queries using these tables are taking too much time, even simple queries like:
"SELECT COUNT(*) FROM MyItemsTable" and "SELECT COUNT(*) FROM MyTransactionsTable"
are taking 10 seconds and 26 seconds
large reports now are taking 15mins !!! toooooo much time.
All the table that I'm using are innodb
is there any way to solve this problem before I read about reputation ??
Thank you in advance for any help
Edit
Here is the structure and indexes of MyItemsTable:
CREATE TABLE `pos_MyItemsTable` (
`itemid` bigint(15) NOT NULL,
`uploadid` bigint(15) NOT NULL,
`itemtypeid` bigint(15) NOT NULL,
`statusid` int(1) NOT NULL,
`uniqueid` varchar(10) DEFAULT NULL,
`referencenb` varchar(30) DEFAULT NULL,
`serialnb` varchar(25) DEFAULT NULL,
`code` varchar(50) DEFAULT NULL,
`user` varchar(16) CHARACTER SET utf8 COLLATE utf8_bin DEFAULT NULL,
`pass` varchar(100) CHARACTER SET utf8 COLLATE utf8_bin DEFAULT NULL,
`expirydate` date DEFAULT NULL,
`userid` bigint(15) DEFAULT NULL,
`insertdate` datetime DEFAULT NULL,
`updateuser` bigint(15) DEFAULT NULL,
`updatedate` datetime DEFAULT NULL,
`counternb` int(1) DEFAULT '0',
PRIMARY KEY (`itemid`),
UNIQUE KEY `referencenb_unique` (`referencenb`),
KEY `MyItemsTable_r04` (`itemtypeid`),
KEY `MyItemsTable_r05` (`uploadid`),
KEY `FK_MyItemsTable` (`statusid`),
KEY `ind_MyItemsTable_serialnb` (`serialnb`),
KEY `uniqueid_key` (`uniqueid`),
KEY `ind_MyItemsTable_insertdate` (`insertdate`),
KEY `ind_MyItemsTable_counternb` (`counternb`),
CONSTRAINT `FK_MyItemsTable` FOREIGN KEY (`statusid`) REFERENCES `MyItemsTable_statuses` (`statusid`),
CONSTRAINT `MyItemsTable_r04` FOREIGN KEY (`itemtypeid`) REFERENCES `itemstypes` (`itemtypeid`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `MyItemsTable_r05` FOREIGN KEY (`uploadid`) REFERENCES `uploads` (`uploadid`) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB DEFAULT CHARSET=utf8
Just having few indexes does not mean your tables and queries are optimized.
Try to identify the querties that run the slowest and add specific indexes there.
Selecting * from a huge table .. where you have columns that contain text / images / files
will be aways slow. Try to limit the selection of such fat columns when you don't need them.
future readings:
http://dev.mysql.com/doc/refman/5.0/en/innodb-index-types.html
http://www.xaprb.com/blog/2006/07/04/how-to-exploit-mysql-index-optimizations/
and some more advanced configurations:
http://www.mysqlperformanceblog.com/2006/09/29/what-to-tune-in-mysql-server-after-installation/
http://www.mysqlperformanceblog.com/2007/11/03/choosing-innodb_buffer_pool_size/
source
UPDATE:
try to use composite keys for some of the heaviest queries,
by placing the main fields that are compared in ONE index:
`MyItemsTable_r88` (`itemtypeid`,`statusid`, `serialnb`), ...
this will give you faster results for queries that complare only columns from the index :
SELECT * FROM my_table WHERE `itemtypeid` = 5 AND `statusid` = 0 AND `serialnb` > 500
and extreamlly fast if you search and select values from the index:
SELECT `serialnb` FROM my_table WHERE `statusid` = 0 `itemtypeid` IN(1,2,3);
This are really basic examples you will have to read a bit more and analyze the data for the best results.
I am working with mysql .
I have checked the CREATE table statement , and I saw there a KEY word
| pickupspc | CREATE TABLE `pickupspc` (
`McId` int(11) NOT NULL,
`Slot` int(11) NOT NULL,
`FromTime` datetime NOT NULL,
`ToTime` datetime NOT NULL,
`Head` int(11) NOT NULL,
`Nozzle` int(11) DEFAULT NULL,
`FeederID` int(11) DEFAULT NULL,
`CompName` varchar(64) DEFAULT NULL,
`CompID` varchar(32) DEFAULT NULL,
`PickUps` int(11) DEFAULT NULL,
`Errors` int(11) DEFAULT NULL,
`ErrorCode` varchar(32) DEFAULT NULL,
KEY `ndx_PickupSPC` (`McId`,`Slot`,`FromTime`,`ToTime`,`Head`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1 |
But what is the meaning of it ?
It's not like a PRIMARY KEY right ?
Thanks .
It is simply a synonym for INDEX. It creates an index with the name ndx_PickupSPC on the columns specified in parenthesis.
See the CREATE TABLE syntax for more information.
It's just a non-unique index. From the manual
KEY is normally a synonym for INDEX. The key attribute PRIMARY KEY can
also be specified as just KEY when given in a column definition. This
was implemented for compatibility with other database systems.
Key and index are the same. The word Key in the table creation is used to create an index, which enables faster performance.
In the above code, Key ndx_PickupSPC means that it is creating an index by the name ndx_PickupSPC on the columns mentioned in parenthesis.
It's an INDEX on the table. Indexes enable fast lookups for specific queries which check the values of the columns the index is built on. The example uses a compound key.
They are a bit similar to the indexes you find at the end of the books. You can quickly find an entry with the index without searching through the whole book. Databases typically use B-Trees for indexes.