40 million tables in MySQL 8.0 with ZFS

40 million tables in MySQL 8

40 million tables in MySQL 8In my previous blog post about millions of table in MySQL 8, I was able to create one million tables and test the performance of it. My next challenge is to create 40 million tables in MySQL 8 using shared tablespaces (one tablespace per schema). In this blog post I’m showing how to do it and what challenges we can expect.

Background

Once again – why do we need so many tables in MySQL, what is the use case? The main reason is: customer isolation. With the new focus on security and privacy (take GDPR for example) it is much easier and more beneficial to create a separate schema (or “database” in MySQL terms) for each customer. That creates a new set of challenges that we will need to solve. Here is the summary:

  1. Too many files. For each table MySQL creates an FRM file. With MySQL 8.0, this is not the case for InnoDB tables (new data dictionary): it does not create FRM files, only creates IBD file.
  2. Too much storage overhead. Just to create 40 million tables we will need to have ~4 – 5 Tb of space. The ZFS filesystem can help here a lot, through compression – see below.
  3. MySQL does not work well with so many tables. We have observed a lot of overhead (MySQL needs to open/close table definition files) and contention (table definitions needs to be stored in memory to avoid performance penalty, which introduce mutex contention)

Challenges

When I approached the task of creating 40 million tables, my first challenge was disk space. Just to create them, I needed at least 5Tb of fast disk storage. The good news is: we have the ZFS filesystem which provides compression out of the box. With compression I was able to use just a 250G drive with ZFS – the compression ratio is > 10x:

# du -sh --apparent-size /var/lib/mysql-data
4.7T    /var/lib/mysql-data
# du -sh /var/lib/mysql-data
131G    /var/lib/mysql-data

The second challenge is how to create those tables in a reasonable amount of time. I created a script to “provision” the databases (create all 40 millions tables). The good new is that the performance regression in “create table” speed and scalability bug was fixed so I was able to use this script to create 40 million tables using shared tablespaces (one tablespace per schema):

#/bin/bash
function do_db {
        db_exist=$(mysql -A -s -Nbe "select 1 from information_schema.schemata where schema_name = '$db'")
        if [ "$db_exist" == "1" ]; then echo "Already exists $db"; return 0; fi;
        mysql -vvv -e "create database $db";
        mysql -vvv $db -e "CREATE TABLESPACE $db ADD DATAFILE '$db.ibd' engine=InnoDB;"
        for i in {1..100}
        do
                table="CREATE TABLE sbtest$i ( id int(10) unsigned NOT NULL AUTO_INCREMENT, k int(10) unsigned NOT NULL DEFAULT '0', c varchar(120) NOT NULL DEFAULT '', pad varchar(60) NOT NULL DEFAULT '', PRIMARY KEY (id), KEY k_1 (k) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 tablespace $db;"
                mysql $db -e "$table"
        done
}
c=0
for m in {1..4000000}
do
        for i in {1..40}
        do
                let c=$c+1
                echo $c
                db="sbtest_$c"
                do_db &
        done
        wait
        #if [ $c > 4000000 ]; then exit; fi
done

40 million tables in MySQL 8

Now it’s time for a real test. I’m using the latest MySQL 8 version (at the time of writing): 8.0.12. This implements the new data dictionary.

MySQL config file:

[mysqld]
datadir=/var/lib/mysql-data
socket=/var/lib/mysql-data/mysql.sock
datadir=/var/lib/mysql-data
log-error = /var/lib/mysql-log/error.log
server_id = 12345
log_bin = /var/lib/mysql-log/binlog
relay_log=/var/lib/mysql-log/relay-bin
skip-log-bin=1
innodb_log_group_home_dir = /var/lib/mysql-log
innodb_doublewrite = 0
innodb_flush_log_at_trx_commit=0
innodb_log_file_size=2G
innodb_buffer_pool_size=4G
tablespace_definition_cache = 524288
schema_definition_cache = 524288
table_definition_cache = 524288
table_open_cache=524288
open-files-limit=1000000

Sysbench shell script:

function run_sb() {
conn=" --db-driver=mysql --mysql-socket=/var/lib/mysql-data/mysql.sock  --mysql-db=sbtest_1 --mysql-user=sbtest --mysql-password=abc "
sysbench $conn --oltp_db_count=$db_count --oltp_tables_count=$table_count --oltp-table-size=10000 --report-interval=1 --num-threads=$num_threads --max-requests=0 --max-time=$max_time ./select_custom.lua run | tee -a sysbench_2.txt
}
let db_count=400000
table_count=100
max_time=10000
num_threads=32
run_sb

Sysbench lua script:

pathtest = "/usr/share/sysbench/tests/include/oltp_legacy/"
if pathtest then
   dofile(pathtest .. "common.lua")
else
   require("common")
end
function thread_init(thread_id)
   set_vars()
end
function event()
   local table_name
   local i
   local c_val
   local k_val
   local pad_val
   oltp_db_count = tonumber(oltp_db_count) or 1
   -- local oltp_db_count = 4
   table_name = "sbtest_" .. sb_rand(1, oltp_db_count)..".sbtest".. sb_rand(1, oltp_tables_count)
   k_val = sb_rand(1, oltp_table_size)
   c_val = sb_rand_str([[
###########-###########-###########-###########-###########-###########-###########-###########-###########-###########]])
   pad_val = sb_rand_str([[
###########-###########-###########-###########-###########]])
      rs = db_query("SELECT id FROM " .. table_name .." LIMIT 1")
end

Please note that the tables are empty – no data.

Now we can run the benchmark. Unfortunately, we have a serious mutex contention in the data dictionary. Here are the results:

[ 453s ] thds: 32 tps: 1203.96 qps: 1203.96 (r/w/o: 1203.96/0.00/0.00) lat (ms,95%): 41.10 err/s: 0.00 reconn/s: 0.00
[ 454s ] thds: 32 tps: 1202.32 qps: 1202.32 (r/w/o: 1202.32/0.00/0.00) lat (ms,95%): 42.61 err/s: 0.00 reconn/s: 0.00
[ 455s ] thds: 32 tps: 1196.74 qps: 1196.74 (r/w/o: 1196.74/0.00/0.00) lat (ms,95%): 41.10 err/s: 0.00 reconn/s: 0.00
[ 456s ] thds: 32 tps: 1197.18 qps: 1197.18 (r/w/o: 1197.18/0.00/0.00) lat (ms,95%): 41.10 err/s: 0.00 reconn/s: 0.00
[ 457s ] thds: 32 tps: 887.11 qps: 887.11 (r/w/o: 887.11/0.00/0.00) lat (ms,95%): 41.10 err/s: 0.00 reconn/s: 0.00
[ 458s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 459s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 460s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 461s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 462s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 463s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 464s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 465s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 466s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 467s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 468s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 469s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 470s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 471s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 472s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 473s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 474s ] thds: 32 tps: 403.96 qps: 403.96 (r/w/o: 403.96/0.00/0.00) lat (ms,95%): 16819.24 err/s: 0.00 reconn/s: 0.00
[ 475s ] thds: 32 tps: 1196.00 qps: 1196.00 (r/w/o: 1196.00/0.00/0.00) lat (ms,95%): 41.85 err/s: 0.00 reconn/s: 0.00
[ 476s ] thds: 32 tps: 1208.96 qps: 1208.96 (r/w/o: 1208.96/0.00/0.00) lat (ms,95%): 41.85 err/s: 0.00 reconn/s: 0.00
[ 477s ] thds: 32 tps: 1192.06 qps: 1192.06 (r/w/o: 1192.06/0.00/0.00) lat (ms,95%): 41.85 err/s: 0.00 reconn/s: 0.00
[ 478s ] thds: 32 tps: 1173.89 qps: 1173.89 (r/w/o: 1173.89/0.00/0.00) lat (ms,95%): 43.39 err/s: 0.00 reconn/s: 0.00

As we can see, for ~15 seconds no queries were processed: a complete MySQL stall. That situation – complete stall – happens constantly, every ~25-30 seconds.

Show engine innodb status query shows mutex contention:

SEMAPHORES
----------
OS WAIT ARRAY INFO: reservation count 498635
--Thread 140456572004096 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140451898689280 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140451896919808 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140456571119360 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140457044215552 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140456572299008 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140457043035904 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140456571709184 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140451897214720 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140451896624896 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140457042740992 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140451899279104 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
--Thread 140457042446080 has waited at que0que.cc line 1072 for 0.00 seconds the semaphore:
Mutex at 0x34a3fe0, Mutex PARSER created pars0pars.cc:98, lock var 1
OS WAIT ARRAY INFO: signal count 89024
RW-shared spins 11216, rounds 14847, OS waits 3641

I’ve filed a  new MySQL bug: DICT_SYS mutex contention causes complete stall when running with 40 mill tables.

I’ve also tested with pareto distribution in sysbench, and even set the ratio to 0.05 (5%) and 0.01 (1%), and mutex contention is still an issue. I have used the following updated sysbench script:

function run_sb() {
conn=" --db-driver=mysql --mysql-socket=/var/lib/mysql-data/mysql.sock  --mysql-db=sbtest_1 --mysql-user=sbtest --mysql-password=abc "
sysbench $conn --rand-type=$rand_type --rand-pareto-h=$pareto_h --oltp_db_count=$db_count --oltp_tables_count=$table_count --oltp-table-size=10000 --report-interval=1 --num-threads=$num_threads --max-requests=0 --max-time=$max_time $test_name run | tee -a sysbench_2.txt
}
let db_count=400000
table_count=100
max_time=10000
num_threads=32
rand_type="pareto"
pareto_h=0.01
test_name="./select_custom.lua"
echo "Now running $rand_type for $max_time seconds, test=$test_name"
run_sb

And the results with 0.01 (1%) are the following:

[ 55s ] thds: 32 tps: 72465.29 qps: 72465.29 (r/w/o: 72465.29/0.00/0.00) lat (ms,95%): 0.53 err/s: 0.00 reconn/s: 0.00
[ 56s ] thds: 32 tps: 68641.04 qps: 68641.04 (r/w/o: 68641.04/0.00/0.00) lat (ms,95%): 0.61 err/s: 0.00 reconn/s: 0.00
[ 57s ] thds: 32 tps: 70479.82 qps: 70479.82 (r/w/o: 70479.82/0.00/0.00) lat (ms,95%): 0.57 err/s: 0.00 reconn/s: 0.00
[ 58s ] thds: 32 tps: 31395.55 qps: 31395.55 (r/w/o: 31395.55/0.00/0.00) lat (ms,95%): 0.49 err/s: 0.00 reconn/s: 0.00
[ 59s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 60s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 61s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 62s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 63s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 64s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 65s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 66s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 67s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 68s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 69s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 70s ] thds: 32 tps: 0.00 qps: 0.00 (r/w/o: 0.00/0.00/0.00) lat (ms,95%): 0.00 err/s: 0.00 reconn/s: 0.00
[ 71s ] thds: 32 tps: 18879.04 qps: 18879.04 (r/w/o: 18879.04/0.00/0.00) lat (ms,95%): 0.75 err/s: 0.00 reconn/s: 0.00
[ 72s ] thds: 32 tps: 70924.82 qps: 70924.82 (r/w/o: 70924.82/0.00/0.00) lat (ms,95%): 0.48 err/s: 0.00 reconn/s: 0.00
[ 73s ] thds: 32 tps: 72395.57 qps: 72395.57 (r/w/o: 72395.57/0.00/0.00) lat (ms,95%): 0.47 err/s: 0.00 reconn/s: 0.00
[ 74s ] thds: 32 tps: 72483.22 qps: 72484.22 (r/w/o: 72484.22/0.00/0.00) lat (ms,95%): 0.58 err/s: 0.00 reconn/s: 0.00

ZFS

The ZFS filesystem provides compression, which helps tremendously in this case. When MySQL creates an InnoDB table it will create a new blank .ibd file and pre-allocate some pages, which will be blank. I have configured ZFS compression and can see > 10x compression ratio:

# zfs get all | grep compressratio
mysqldata                       compressratio         12.47x                      -
mysqldata                       refcompressratio      1.00x                       -
mysqldata/mysql                 compressratio         12.47x                      -
mysqldata/mysql                 refcompressratio      1.00x                       -
mysqldata/mysql/data            compressratio         12.51x                      -
mysqldata/mysql/data            refcompressratio      12.54x                      -
mysqldata/mysql/log             compressratio         2.79x                       -
mysqldata/mysql/log             refcompressratio      4.57x                       -

Conclusion

It is possible to create 40 million tables with MySQL 8.0 using shared tablespaces. ZFS provides an excellent compression ratio (with gzip) which can help by reducing the overhead of “schema per customer” architecture. Unfortunately, the new data dictionary in MySQL 8.0.12 suffers from the DICT_SYS mutex contention and causes constant “stalls”.

The post 40 million tables in MySQL 8.0 with ZFS appeared first on Percona Database Performance Blog.

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