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MySQL “IN” operator performance on (large?) number of values

Posted by: admin November 1, 2017 Leave a comment

Questions:

I have been experimenting with Redis and MongoDB lately and it would seem that there are often cases where you would store an array of id’s in either MongoDB or Redis. I’ll stick with Redis for this question since I am asking about the MySQL IN operator.

I was wondering how performant it is to list a large number (300-3000) of id’s inside the IN operator, which would look something like this:

SELECT id, name, price
FROM products
WHERE id IN (1, 2, 3, 4, ...... 3000)

Imagine something as simple as a products and categories table which you might normally JOIN together to get the products from a certain category. In the example above you can see that under a given category in Redis ( category:4:product_ids ) I return all the product ids from the category with id 4, and place them in the above SELECT query inside the IN operator.

How performant is this?

Is this an “it depends” situation? Or is there a concrete “this is (un)acceptable” or “fast” or “slow” or should I add a LIMIT 25, or doesn’t that help?

SELECT id, name, price
FROM products
WHERE id IN (1, 2, 3, 4, ...... 3000)
LIMIT 25

Or should I trim the array of product id’s returned by Redis to limit it to 25 and only add 25 id’s to the query rather than 3000 and LIMIT-ing it to 25 from inside the query?

SELECT id, name, price
FROM products
WHERE id IN (1, 2, 3, 4, ...... 25)

Any suggestions/feedback is much appreciated!

Answers:

Generally speaking, if the IN list gets too large (for some ill-defined value of ‘too large’ that is usually in the region of 100 or smaller), it becomes more efficient to use a join, creating a temporary table if need so be to hold the numbers.

If the numbers are a dense set (no gaps – which the sample data suggests), then you can do even better with WHERE id BETWEEN 300 AND 3000. However, presumably there are gaps in the set, at which point it may be better to go with the list of valid values after all (unless the gaps are relatively few in number, in which case you could use: WHERE id BETWEEN 300 AND 3000 AND id NOT BETWEEN 742 AND 836 or whatever the gaps are.

Questions:
Answers:

I have been doing some tests, and as David Fells says, it is quite well optimized. As a reference, I have created an InnoDB table with 1000000 registers and doing a select with the “IN” operator with 500000 random numbers, it takes only 2,5s in my MAC. (Selecting only the even registers takes 0,5s).

The only problem that I had is that I had to increase the max_allowed_packet parameter from the my.cnf file. If not, a mysterious “MYSQL has gone away” error is generated.

Here is the PHP code that I use to make the test:

$NROWS =1000000;
$SELECTED = 50;
$NROWSINSERT =15000;

$dsn="mysql:host=localhost;port=8889;dbname=testschema";
$pdo = new PDO($dsn, "root", "root");
$pdo->setAttribute(PDO::ATTR_ERRMODE, PDO::ERRMODE_EXCEPTION);

$pdo->exec("drop table if exists `uniclau`.`testtable`");
$pdo->exec("CREATE  TABLE `testtable` (
        `id` INT NOT NULL ,
        `text` VARCHAR(45) NULL ,
        PRIMARY KEY (`id`) )");

$before = microtime(true);

$Values='';
$SelValues='(';
$c=0;
for ($i=0; $i<$NROWS; $i++) {
    $r = rand(0,99);
    if ($c>0) $Values .= ",";
    $Values .= "( $i , 'This is value $i and r= $r')";
    if ($r<$SELECTED) {
        if ($SelValues!="(") $SelValues .= ",";
        $SelValues .= $i;
    }
    $c++;

    if (($c==100)||(($i==$NROWS-1)&&($c>0))) {
        $pdo->exec("INSERT INTO `testtable` VALUES $Values");
        $Values = "";
        $c=0;
    }
}
$SelValues .=')';
echo "<br>";


$after = microtime(true);
echo "Insert execution time =" . ($after-$before) . "s<br>";

$before = microtime(true);  
$sql = "SELECT count(*) FROM `testtable` WHERE id IN $SelValues";
$result = $pdo->prepare($sql);  
$after = microtime(true);
echo "Prepare execution time =" . ($after-$before) . "s<br>";

$before = microtime(true);

$result->execute();
$c = $result->fetchColumn();

$after = microtime(true);
echo "Random selection = $c Time execution time =" . ($after-$before) . "s<br>";



$before = microtime(true);

$sql = "SELECT count(*) FROM `testtable` WHERE id %2 = 1";
$result = $pdo->prepare($sql);
$result->execute();
$c = $result->fetchColumn();

$after = microtime(true);
echo "Pairs = $c Exdcution time=" . ($after-$before) . "s<br>";

And the results:

Insert execution time =35.2927210331s
Prepare execution time =0.0161771774292s
Random selection = 499102 Time execution time =2.40285992622s
Pairs = 500000 Exdcution time=0.465420007706s

Questions:
Answers:

IN is fine, and well optimized. Make sure you use it on an indexed field and you’re fine. It’s functionally equivalent to (x = 1 OR x = 2 OR x = 3 … OR x = 99) as far as the engine’s concerned.

Questions:
Answers:

You can create a temporary table where you can put any number of IDs and run nested query
Example:

CREATE [TEMPORARY] TABLE tmp_IDs (`ID` INT NOT NULL,PRIMARY KEY (`ID`));

and select:

SELECT id, name, price
FROM products
WHERE id IN (SELECT ID FROM tmp_IDs);

Questions:
Answers:

Using IN with a large parameter set on a large list of records will in fact be slow.

In the case that I solved recently I had two where clauses, one with 250 parameters and the other with 3500 parameters, querying a table of 40 Million records. My query took 5 minutes using the standard WHERE IN. By instead using a subquery for the IN statement(putting the parameters in their own indexed table), I got the query down to TWO seconds. Worked for both MySQL and Oracle in my experience.

Questions:
Answers:

When you provide many values for the IN operator it first must sort it to remove duplicates. At least I suspect that. So it would be not good to provide too many values, as sorting takes N log N time.

My experience proved that slicing the set of values into smaller subsets and combining the results of all the queries in the application gives best performance. I admit that I gathered experience on a different database (Pervasive), but the same may apply to all the engines. My count of values per set was 500-1000. More or less was significantly slower.