The document describes the evolution of import tools for Magento over time from 2008-2019. It discusses early sequential import methods that took 20+ minutes for 5k products. Later improvements included storing data in batches, using multi-row inserts, and processing without the product model to increase speeds to 41-450 products/second. The latest method discussed asynchronously processes separate feeds concurrently using multiple database connections and prepared statements, achieving speeds over 1,850 products/second and importing 1 million SKUs in under 10 minutes.

1. How to import 1 million SKUs
in under 10 minutes
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2. Building an import correctly is hard
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3. 2008
it all started with
DataFlow
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4. DataFlow
4/26

5. DataFlow
Stores CSV
records into
database
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6. DataFlow
Stores CSV
records into
database
Imports product
by product via
AJAX call
4/26

7. DataFlow
Stores CSV
records into
database
Imports product
by product via
AJAX call
Uses product
model to save
data
4/26

8. DataFlow
Stores CSV
records into
database
Imports product
by product via
AJAX call
Uses product
model to save
data
Closing the
browser window
stops the whole
process
4/26

9. Speed
2-3 products per second
5/26

10. Speed
2-3 products per second
~ 20 minutes for 5k products
5/26

11. 2011
Import/Export saved us all
6/26

12. ImportExport
7/26

13. ImportExport
Stored batches of
data into the
database during
validation
7/26

14. ImportExport
Stored batches of
data into the
database during
validation
Processes stored
data in one HTTP
request
7/26

15. ImportExport
Stored batches of
data into the
database during
validation
Processes stored
data in one HTTP
request
Validates product
data without using
product model
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16. ImportExport
Stored batches of
data into the
database during
validation
Processes stored
data in one HTTP
request
Validates product
data without using
product model
Uses multi-row
inserts to
populate tables
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17. ImportExport
Stored batches of
data into the
database during
validation
Processes stored
data in one HTTP
request
Validates product
data without using
product model
Uses multi-row
inserts to
populate tables
Does not run
indexers
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18. Speed
41 product per second
8/26

19. Speed
41 product per second
~ 2 minutes for 5k products
8/26

20. But there are some
drawbacks
9/26

21. High memory usage on large datasets
But there are some
drawbacks
9/26

22. High memory usage on large datasets
Slow in generating primary keys for new products
But there are some
drawbacks
9/26

23. 2015
Magento 2.x
Import Export
10/26

24. ImportExport M2
11/26

25. Same base functionality as in M1
ImportExport M2
11/26

26. Same base functionality as in M1
More complex file format to edit and parse
ImportExport M2
11/26

27. Same base functionality as in M1
More complex file format to edit and parse
Slower on complex product data
ImportExport M2
11/26

28. Same base functionality as in M1
More complex file format to edit and parse
Slower on complex product data
Adds additional single statement inserts
ImportExport M2
11/26

29. 2019
I got an idea and a project to implement it on
12/26

30. Separate Feeds
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31. Separate Feeds
Main entity (sku, type, set)
13/26

32. Separate Feeds
Main entity (sku, type, set)
Attributes (sku, attribute, store, value)
13/26

33. Separate Feeds
Main entity (sku, type, set)
Attributes (sku, attribute, store, value)
Category (sku, category slug, position)
13/26

34. Separate Feeds
Main entity (sku, type, set)
Attributes (sku, attribute, store, value)
Category (sku, category slug, position)
Configurable Options (sku, attribute, label)
13/26

35. Separate Feeds
Main entity (sku, type, set)
Attributes (sku, attribute, store, value)
Category (sku, category slug, position)
Configurable Options (sku, attribute, label)
Images (sku, image)
13/26

36. Separate Feeds
Main entity (sku, type, set)
Attributes (sku, attribute, store, value)
Category (sku, category slug, position)
Configurable Options (sku, attribute, label)
Images (sku, image)
...
13/26

37. Lazy Entity Resolving
14/26

38. Lazy Entity Resolving
Reduce memory requirements of the import
14/26

39. Lazy Entity Resolving
Reduce memory requirements of the import
Cleaner and more readable feed processing
14/26

40. Lazy Entity Resolving
Reduce memory requirements of the import
Cleaner and more readable feed processing
Possibility of acquiring entity ids in batches
automatically
14/26

41. Lazy Entity Resolving
$resolver = $this->resolverFactory->createSingleValueResolver(
'catalog_product_entity', 'sku', 'entity_id'
);
$insert = InsertOnDuplicate::create(
'catalog_product_entity_varchar',
['entity_id', 'attribute_id', 'store_id', 'value']
)->withResolver($resolver);
$insert
->withRow($resolver->unresolved('sku1'), 1, 0, 'some value')
->withRow($resolver->unresolved('sku2'), 1, 0, 'some value1')
->withRow($resolver->unresolved('sku3'), 1, 0, 'some value2');
15/26

42. Configure table lookup information
Lazy Entity Resolving
$resolver = $this->resolverFactory->createSingleValueResolver(
'catalog_product_entity', 'sku', 'entity_id'
);
$insert = InsertOnDuplicate::create(
'catalog_product_entity_varchar',
['entity_id', 'attribute_id', 'store_id', 'value']
)->withResolver($resolver);
$insert
->withRow($resolver->unresolved('sku1'), 1, 0, 'some value')
->withRow($resolver->unresolved('sku2'), 1, 0, 'some value1')
->withRow($resolver->unresolved('sku3'), 1, 0, 'some value2');
15/26

43. Pass resolver into insert builder
Lazy Entity Resolving
$insert = InsertOnDuplicate::create(
'catalog_product_entity_varchar',
['entity_id', 'attribute_id', 'store_id', 'value']
)->withResolver($resolver);
$resolver = $this->resolverFactory->createSingleValueResolver(
'catalog_product_entity', 'sku', 'entity_id'
);
$insert
->withRow($resolver->unresolved('sku1'), 1, 0, 'some value')
->withRow($resolver->unresolved('sku2'), 1, 0, 'some value1')
->withRow($resolver->unresolved('sku3'), 1, 0, 'some value2');
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44. Use resolver to create identifier containers
Lazy Entity Resolving
->withRow($resolver->unresolved('sku1'), 1, 0, 'some value')
->withRow($resolver->unresolved('sku2'), 1, 0, 'some value1')
->withRow($resolver->unresolved('sku3'), 1, 0, 'some value2');
$resolver = $this->resolverFactory->createSingleValueResolver(
'catalog_product_entity', 'sku', 'entity_id'
);
$insert = InsertOnDuplicate::create(
'catalog_product_entity_varchar',
['entity_id', 'attribute_id', 'store_id', 'value']
)->withResolver($resolver);
$insert
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45. Insert on duplicate will skip any unresolved entries
Lazy Entity Resolving
$resolver = $this->resolverFactory->createSingleValueResolver(
'catalog_product_entity', 'sku', 'entity_id'
);
$insert = InsertOnDuplicate::create(
'catalog_product_entity_varchar',
['entity_id', 'attribute_id', 'store_id', 'value']
)->withResolver($resolver);
$insert
->withRow($resolver->unresolved('sku1'), 1, 0, 'some value')
->withRow($resolver->unresolved('sku2'), 1, 0, 'some value1')
->withRow($resolver->unresolved('sku3'), 1, 0, 'some value2');
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46. 16/26

47. Batch auto-increment generation
START TRANSACTION;
INSERT INTO catalog_product_entity (sku)
VALUES
('sku1'),
('sku2'),
('sku3'),
('sku4');
SELECT entity_id, sku
FROM catalog_product_entity
WHERE
sku IN ('sku1', 'sku2', 'sku3', 'sku4');
ROLLBACK;
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48. Start a transaction
Batch auto-increment generation
START TRANSACTION;
INSERT INTO catalog_product_entity (sku)
VALUES
('sku1'),
('sku2'),
('sku3'),
('sku4');
SELECT entity_id, sku
FROM catalog_product_entity
WHERE
sku IN ('sku1', 'sku2', 'sku3', 'sku4');
ROLLBACK;
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49. Populate table with un-resolved keys
Batch auto-increment generation
INSERT INTO catalog_product_entity (sku)
VALUES
('sku1'),
('sku2'),
('sku3'),
('sku4');
START TRANSACTION;
SELECT entity_id, sku
FROM catalog_product_entity
WHERE
sku IN ('sku1', 'sku2', 'sku3', 'sku4');
ROLLBACK;
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50. Retrieve new identifiers
Batch auto-increment generation
SELECT entity_id, sku
FROM catalog_product_entity
WHERE
sku IN ('sku1', 'sku2', 'sku3', 'sku4');
START TRANSACTION;
INSERT INTO catalog_product_entity (sku)
VALUES
('sku1'),
('sku2'),
('sku3'),
('sku4');
ROLLBACK;
17/26

51. Rollback transaction
Batch auto-increment generation
ROLLBACK;
START TRANSACTION;
INSERT INTO catalog_product_entity (sku)
VALUES
('sku1'),
('sku2'),
('sku3'),
('sku4');
SELECT entity_id, sku
FROM catalog_product_entity
WHERE
sku IN ('sku1', 'sku2', 'sku3', 'sku4');
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52. Prepared Statements
18/26

53. Compile query for constant batch size
Prepared Statements
18/26

54. Compile query for constant batch size
Send only data instead of generating new queries
Prepared Statements
18/26

55. Compile query for constant batch size
Send only data instead of generating new queries
Reduces query processing on MySQL side by half
Prepared Statements
18/26

56. Speed
450 products per second
19/26

57. Speed
450 products per second
~ 11 seconds for 5k products
19/26

58. But it was still not good enough
20/26

59. But it was still not good enough
45 minutes to import 1 million SKUs
20/26

60. Sure, because it's a sequential process...
21/26

61. So I made it asynchronous as PoC
22/26

62. Under the hood
23/26

63. Under the hood
Each target tabletarget table receives a separate connection
to MySQL
23/26

64. Under the hood
Each target tabletarget table receives a separate connection
to MySQL
Identity resolver is attached to the source table
connection
23/26

65. Under the hood
Each target tabletarget table receives a separate connection
to MySQL
Identity resolver is attached to the source table
connection
Each feed is processed concurrently by using
round robinround robin strategy
23/26

66. Under the hood
Each target tabletarget table receives a separate connection
to MySQL
Identity resolver is attached to the source table
connection
Each feed is processed concurrently by using
round robinround robin strategy
During MySQL query execution PHP prepares the
next batch
23/26

67. Speed
1,850 products per second
24/26

68. Speed
1,850 products per second
~ 9 minutes for 1m products
24/26

69. It is coming this fall as an open source tool for
everyone!
25/26

70. Questions
ivan@ecomdev.org
IvanChepurnyi.GitHub.io
26/26