Bill Karwin's presentation at the Percona Live Open Source Database Conference 2017 focuses on strategies for efficiently loading data into MySQL databases. He discusses various techniques including schema modifications, query optimizations, and configuration tweaks to enhance performance, illustrating with performance metrics from different insertion methods. The talk concludes with insights on parallel execution and the importance of benchmarking to find the best approach for specific use cases.

1. Load Data Fast!
BILL KARWIN
PERCONA LIVE OPEN SOURCE DATABASE CONFERENCE 2017

2. Bill Karwin
Software developer, consultant, trainer
Using MySQL since 2000
Senior Database Architect at SchoolMessenger
SQL Antipatterns: Avoiding the Pitfalls of Database
Programming
https://pragprog.com/titles/bksqla/sql-antipatterns
Oracle ACE Director

3. Load Data Fast!
Common chores
§ Dump and restore
§ Import third-party data
§ Extract, Transfer, Load (ETL)
§ Test data that needs to be reloaded
repeatedly
https://commons.wikimedia.org/wiki/File:Kitten_with_laptop_-_278017185.jpg
Is it done yet?

4. How to Speed This Up?
1. Query Solutions
2. Schema Solutions
3. Configuration Solutions
4. Parallel Execution Solutions

5. Example Table
CREATE TABLE TestTable (
id INT UNSIGNED NOT NULL PRIMARY KEY,
intCol INT UNSIGNED DEFAULT NULL,
stringCol VARCHAR(100) DEFAULT NULL,
textCol TEXT
) ENGINE=InnoDB;
Let’s load 1 million rows!

6. Best Case Performance
Running a test script to loop over 1 million rows, without inserting to a database.
$ php test-bulk-insert.php --total-rows 1000000 --noop
This should have a speed that is the upper bound for any subsequent test.
Time: 2 seconds (00:00:02)
1000000 rows = 432435.24 rows/sec
1000000 stmt = 432435.24 stmt/sec
1000000 txns = 432435.24 txns/sec
1000000 conn = 432435.24 conn/sec

7. Worst Case Performance
INSERT INTO TestTable (id, intCol, stringCol, textCol) VALUES
(?, ?, ?, ?);
Run a test script that executes one INSERT, commits, reconnects.
$ php test-bulk-insert.php --total-rows 10000
Time: 34 seconds (00:00:34)
10000 rows = 290.29 rows/sec
10000 stmt = 290.29 stmt/sec
10000 txns = 290.29 txns/sec
10000 conn = 290.29 conn/sec

8. Inserting One Row: Overhead
https://dev.mysql.com/doc/refman/8.0/en/insert-optimization.html
0
0.5
1
1.5
2
2.5
3
Connecting Sending query Parsing Inserting row Closing query

9. Query Solutions

10. Inserting One Row at a Time
INSERT INTO TestTable (id, intCol, stringCol, textCol) VALUES
(?, ?, ?, ?);
Run a test script that executes one INSERT, commits using a single connection.
$ php test-bulk-insert.php --total-rows 1000000
--txns-per-conn 1000000
Time: 527 seconds (00:08:47)
1000000 rows = 1894.67 rows/sec
1000000 stmt = 1894.67 stmt/sec
1000000 txns = 1894.67 txns/sec
1 conn = 0.00 conn/sec

11. Inserting One Row: Overhead
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Sending query Parsing Inserting row Closing query

12. Inserting Multiple Rows
INSERT INTO TestTable (id, intCol, stringCol, textCol) VALUES
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?),
(?, ?, ?, ?);
Q: How many rows can you insert in one statement?
A: As many as fit in max_allowed_packet bytes.

13. Inserting Multiple Rows: Overhead
0
1
2
3
4
5
6
7
8
Sending query Parsing Inserting row Closing query

14. Inserting Multiple Rows: Results
$ php Test-bulk-insert.php --total-rows 1000000
--rows-per-stmt 100 --txns-per-conn 10000
Time: 85 seconds (00:01:25)
1000000 rows = 11680.98 rows/sec
10000 stmt = 116.81 stmt/sec
10000 txns = 116.81 txns/sec
1 conn = 0.01 conn/sec

15. Transactions
BEGIN TRANSACTION;
INSERT INTO TestTable …
INSERT INTO TestTable …
INSERT INTO TestTable …
INSERT INTO TestTable …
INSERT INTO TestTable …
INSERT INTO TestTable …
COMMIT;
Q: How many statements can you do in one transaction?
A: In theory this is constrained by undo log segments, but it's a lot.

16. Transactions: Results
$ php test-bulk-insert.php --total-rows 1000000
--rows-per-stmt 100 --stmts-per-txn 100 --txns-per-conn 100
Time: 63 seconds (00:01:03)
1000000 rows = 15744.53 rows/sec
10000 stmt = 157.45 stmt/sec
100 txns = 1.57 txns/sec
1 conn = 0.02 conn/sec

17. Inserting with Prepared Queries
BEGIN TRANSACTION;
PREPARE INSERT INTO TestTable …
EXECUTE …
EXECUTE …
EXECUTE …
EXECUTE …
COMMIT;
Q: How many times can you execute a given prepared statement?
A: There is no limit, as far as I can tell.

18. 0
1
2
3
4
5
6
7
8
Sending query Parsing Inserting row Inserting row Inserting row Inserting row Closing query
Prepared Queries: Overhead

19. Prepared Queries: Results
$ php test-bulk-insert.php --total-rows 1000000
--rows-per-stmt 100 --stmts-per-txn 100 --txns-per-conn 100
$ php test-bulk-insert.php --total-rows 1000000
--rows-per-stmt 100 --stmts-per-txn 100 --txns-per-conn 100
--emulate-prepares
Time: 95 seconds (00:01:35)
1000000 rows = 10518.97 rows/sec
Time: 63 seconds (00:01:03)
1000000 rows = 15744.53 rows/sec

20. Load Data in File: Results
mysql> LOAD DATA LOCAL INFILE 'TestTable.csv'
INTO TABLE TestTable;
https://dev.mysql.com/doc/refman/8.0/en/load-data.html
Flat-file data load in a single transaction.
Works with replication.

21. Overhead: Load Data Infile
0
50
100
150
200
250
Sending query Parsing LOAD DATA INFILE Closing query

22. Load Data in File: Results
$ php test-bulk-insert.php --total-rows 1000000 --load-data
Time: 25 seconds (00:00:25)
1000000 rows = 39563.53 rows/sec
1 stmt = 0.04 stmt/sec
1 txns = 0.04 txns/sec
1 conn = 0.04 conn/sec

23. Load XML in File: Results
LOAD XML LOCAL INFILE 'TestTable.xml'
INTO TABLE TestTable;
https://dev.mysql.com/doc/refman/8.0/en/load-xml.html
$ php test-bulk-insert.php --total-rows 1000000 --load-xml
Time: 77 seconds (00:01:17)
1000000 rows = 12858.16 rows/sec
1 stmt = 0.01 stmt/sec
1 txns = 0.01 txns/sec
1 conn = 0.01 conn/sec

24. What about Load JSON in File?
Sorry, the hypothetical LOAD JSON INFILE is not supported by MySQL yet.
😭
But it has been proposed as a feature request:
https://bugs.mysql.com/bug.php?id=79209
Go vote for it!
Or better yet, implement it and contribute a patch!

25. Schema Solutions

26. Indexes
How much overhead for one index? Two indexes?
1. mysql> ALTER TABLE TestTable ADD INDEX (intCol);
2. mysql> ALTER TABLE TextTable ADD INDEX (stringCol);

27. Indexes: Overhead
0
1
2
3
4
5
6
7
8
Sending query Parsing Inserting row Inserting indexes Closing query

28. Indexes: Results
$ php test-bulk-insert.php --total-rows 1000000 --rows-per-stmt 100
--stmts-per-txn 100 --txns-per-conn 100
$ php test-bulk-insert.php --total-rows 1000000 --rows-per-stmt 100
--stmts-per-txn 100 --txns-per-conn 100 --indexes 1
$ php test-bulk-insert.php --total-rows 1000000 --rows-per-stmt 100
--stmts-per-txn 100 --txns-per-conn 100 --indexes 2
Time: 71 seconds (00:01:11)
1000000 rows = 13993.81 rows/sec
Time: 63 seconds (00:01:03)
1000000 rows = 15744.53 rows/sec
Time: 95 seconds (00:01:35)
1000000 rows = 10473.64 rows/sec

29. Index Deferral
What if we insert with no indexes, and build indexes at the end?
§ Thi is what Percona’s mysqldump --innodb-optimize-keys does.
§ Load time is like when you have no indexes:
Then create indexes after data load. This reduces the effective rate of rows/second:
mysql> ALTER TABLE TestTable ADD INDEX (intCol);
Query OK, 0 rows affected (7.02 sec)
mysql> ALTER TABLE TestTable ADD INDEX (stringCol);
Query OK, 0 rows affected (8.54 sec)
Time: 63 seconds (00:01:03)
1000000 rows = 15744.53 rows/sec
Time: 63 + 7 + 8.5 seconds (00:01:35)
1000000 rows = 12738.85 rows/sec
effective data
load rate

30. Triggers
How much overhead for a trigger?
mysql> CREATE TRIGGER TestTrigger
BEFORE INSERT ON TestTable
FOR EACH ROW
SET NEW.stringCol = UPPER(NEW.stringCol);
This is a very simple trigger. If you have more complex code, like subordinate
INSERT statements, the cost will be higher.

31. Triggers: Results
$ php test-bulk-insert.php --total-rows 1000000
--rows-per-stmt 100 --stmts-per-txn 100 --txns-per-conn 100
--trigger
Time: 69 seconds (00:01:09)
1000000 rows = 14296.91 rows/sec
10000 stmt = 142.97 stmt/sec
100 txns = 1.43 txns/sec
1 conn = 0.01 conn/sec

32. CSV Storage Engine
mysql> CREATE TABLE TestTable (
id INT UNSIGNED NOT NULL,
intCol INT UNSIGNED NOT NULL,
stringCol VARCHAR(100) NOT NULL,
textCol TEXT NOT NULL
) ENGINE=CSV;
# ls -l /usr/local/mysql/data/test
total 24
-rw-r----- 1 _mysql _mysql 5824 Apr 22 20:10 TestTable_429.SDI
-rw-r----- 1 _mysql _mysql 35 Apr 22 20:10 testtable.CSM
-rw-r----- 1 _mysql _mysql 0 Apr 22 20:10 testtable.CSV

33. CSV Storage Engine
Move CSV file into datadir:
# time cp data.csv /usr/local/mysql/data/test/testtable.CSV
real 0m8.359s
# ls -l /usr/local/mysql/data/test/
total 6350872
-rw-r----- 1 _mysql _mysql 5824 Apr 22 20:18 TestTable_431.SDI
-rw-r----- 1 _mysql _mysql 35 Apr 22 20:18 testtable.CSM
-rw-r----- 1 _mysql _mysql 3251630334 Apr 22 20:19 testtable.CSV
Time: 8.359 (00:00:08)
1000000 rows = 119631.53 rows/sec

34. CSV into InnoDB Storage Engine
Use CSV storage engine, then alter to InnoDB table (and add a primary key):
ALTER TABLE TestTable ADD PRIMARY KEY (id), ENGINE=InnoDB;
Query OK, 1000000 rows affected (1 min 37.73 sec)
Time: 8.359 + 97.73 seconds (00:01:46)
1000000 rows = 9426.05 rows/sec
effective data
load rate

35. Partitioning

36. Transportable Tablespaces

37. Configuration Solutions

38. Increase Buffering,
Decrease Durability
innodb_buffer_pool_size = 4G
(default 128M)
innodb_log_buffer_size = 1G
(default 16M)
innodb_log_file_size = 4G
(default 48M)
innodb_flush_log_at_trx_commit = 0
(default 1)
# log-bin = mysql-bin
Time: 56 seconds (00:00:56)
1000000 rows = 17697.29 rows/sec

39. Increase Buffering,
Decrease Durability
Same, but at least flush the log buffer:
innodb_flush_log_at_trx_commit = 2
(default 1)
Time: 60 seconds (00:01:00)
1000000 rows = 16564.26 rows/sec

40. Tuning + Load Data
$ php test-bulk-insert.php --total-rows 1000000 --load-data
Time: 22 seconds (00:00:22)
1000000 rows = 43873.50 rows/sec

41. Config for More Buffering
Innodb_buffer_pool_size=4G
(default 128M)
Time: 82 seconds (00:01:22)
1000000 rows = 12161.69 rows/sec
Innodb_change_buffering=none
(default all)
Innodb_log_buffer_size=1G
(default 16M)
Time: 81 seconds (00:01:21)
1000000 rows = 12291.17 rows/sec
Binlog_cache_size=256K)
(default 32K)

42. Config for Greater Throughput
Innodb_log_file_size=4G
(default 48M)
Time: 80 seconds (00:01:20)
1000000 rows = 12488.30 rows/sec
Innodb_io_capacity=2000
(default 200)
Time: 80 seconds (00:01:20)
1000000 rows = 12432.38 rows/sec
Innodb_lru_scan_depth=8192
(default 1024)
Time: 81 seconds (00:01:21)
1000000 rows = 12269.61 rows/sec

43. Config for Lower Durability
Innodb_doublewrite=OFF
(default ON)
Time: 85 seconds (00:01:25)
1000000 rows = 11740.06 rows/sec
Innodb_flush_log_at_trx_commit=0
(default 1)
Time: 84 seconds (00:01:24)
1000000 rows = 11768.51 rows/sec
# Log_bin Time: 82 seconds (00:01:22)
1000000 rows = 12087.97 rows/sec
Sync_binlog=0
(default 1)
Time: 83 seconds (00:01:23)
1000000 rows = 11906.84 rows/sec

44. Config for Fewer Checks
Innodb_checksum_algorithm=none
(default crc32)
Time: 84 seconds (00:01:24)
1000000 rows = 11807.99 rows/sec
Innodb_log_checksums=OFF
(default ON)
Time: 84 seconds (00:01:24)
1000000 rows = 11893.64 rows/sec
Foreign_key_checks=0
(default 1)
Unique_checks=0
(default 1)

45. Parallel Execution
Solutions

46. Parallel Import
Like LOAD DATA INFILE but supports multi-threaded import:
$ mysqlimport --local --use-threads 4
dbname table1 table2 table3 table4
Runs a fixed number of threads, imports one table per thread.
If an import finishes and there are more tables, first available thread does it.
https://dev.mysql.com/doc/refman/8.0/en/mysqlimport.html

47. Parallel Import
Connecting to localhost
Connecting to localhost
Connecting to localhost
Connecting to localhost
Selecting database test
Selecting database test
Selecting database test
Selecting database test
Loading data from LOCAL file: TestTable2.csv into TestTable2
Loading data from LOCAL file: TestTable3.csv into TestTable3
Loading data from LOCAL file: TestTable1.csv into TestTable1
Loading data from LOCAL file: TestTable4.csv into TestTable4
test.TestTable3: Records: 250000 Deleted: 0 Skipped: 0 Warnings: 0
Disconnecting from localhost
test.TestTable1: Records: 250000 Deleted: 0 Skipped: 0 Warnings: 0
Disconnecting from localhost
test.TestTable2: Records: 250000 Deleted: 0 Skipped: 0 Warnings: 0
Disconnecting from localhost
test.TestTable4: Records: 250000 Deleted: 0 Skipped: 0 Warnings: 0
Disconnecting from localhost

48. MysqlImport: Results
$ php test-bulk-insert.php --total-rows 1000000 --load-data
--use-threads 4
Time: 31 seconds (00:00:31)
1000000 rows = 32205.28 rows/sec
4 stmt = 0.13 stmt/sec
4 txns = 0.13 txns/sec
4 conn = 0.13 conn/sec

49. Conclusions

50. 0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
Rows per Second
why are
you still
doing this?

51. Want to Try The Tests Yourself?
The test-bulk-insert.php script is available here:
https://github.com/billkarwin/bk-tools

52. One Last Thing…
What Was Our Solution?
We cheated:
§ Load database once.
§ Take a filesystem snapshot.
§ Run tests.
§ Restore from snapshot.
§ Re-run tests.
§ etc.
This is not a good solution for everyone. It worked for one specific use case.

53. License and Copyright
Copyright 2017 Bill Karwin
http://www.slideshare.net/billkarwin
Released under a Creative Commons 3.0 License:
http://creativecommons.org/licenses/by-nc-nd/3.0/
You are free to share—to copy, distribute,
and transmit this work, under the following conditions:
Attribution.
You must attribute this
work to Bill Karwin.
Noncommercial.
You may not use this work
for commercial purposes.
No Derivative Works.
You may not alter,
transform, or build upon
this work.