Introduction
Join
Joining two data frames is a common operation in data processing that combines data from two different sources. Flow PHP implements joins using a hash join algorithm that creates a hash table from the right DataFrame and probes it with rows from the left DataFrame.
Join Methods
join()
Main join method that loads the right DataFrame into memory as a hash table for efficient lookups.
crossJoin() - Cartesian Product
Joins each row from the left side with each row on the right side, creating count(left) * count(right) rows total.
joinEach() - Streaming Join
Right side is dynamically generated for each left row, useful for large right-side datasets that don't fit in memory.
Join Types
Flow PHP supports four join types with specific behaviors:
| Join Type | Description |
|---|---|
Left Join (Join::left) |
Returns all rows from left DataFrame with matching rows from right (or NULL) - Default |
Inner Join (Join::inner) |
Returns only rows that exist in both DataFrames |
Right Join (Join::right) |
Returns all rows from right DataFrame with matching rows from left (or NULL) |
Left Anti Join (Join::left_anti) |
Returns rows from left DataFrame that have NO match in right DataFrame |
Flow uses hash join implementation where hashes are stored in sorted buckets to optimize memory usage and performance.
Example
<?php
$externalProducts = [
['id' => 1, 'sku' => 'PRODUCT01'],
['id' => 2, 'sku' => 'PRODUCT02'],
['id' => 3, 'sku' => 'PRODUCT03'],
];
$internalProducts = [
['id' => 2, 'sku' => 'PRODUCT02'],
['id' => 3, 'sku' => 'PRODUCT03'],
];
data_frame()
->read(from_array($externalProducts))
->join(
data_frame()->read(from_array($internalProducts)),
Expression::on(['id' => 'id']),
Join::left_anti
)
->write(to_output())
->run();
Output:
+----+-----------+
| id | sku |
+----+-----------+
| 1 | PRODUCT01 |
+----+-----------+
1 rows
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