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# PySpark RDD | collectAsMap method

schedule Aug 12, 2023
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PySpark RDD's `collectAsMap(~)` method collects all the elements of a pair RDD in the driver nodelink and converts the RDD into a dictionary.

NOTE

A pair RDD is a RDD that contains a list of tuples.

# Parameters

This method does not take in any parameters.

A dictionary.

# Examples

Consider the following PySpark pair RDD:

``` rdd = sc.parallelize([("a",5),("b",2),("c",3)]) rdd.collect() [('a', 5), ('b', 2), ('c', 3)] ```

Here, we are using the `parallelize(~)` method to create a pair RDD.

## Converting a pair RDD into a dictionary in PySpark

To convert a pair RDD into a dictionary in PySpark, use the `collectAsMap()` method:

``` rdd.collectAsMap() {'a': 5, 'b': 2, 'c': 3} ```
WARNING

Since all the underlying data in the RDD is sent to driver node, you may encounter an `OutOfMemoryError` if the data is too large.

### In case of duplicate keys

When we have duplicate keys, the latter key-value pair will overwrite the former ones:

``` rdd = sc.parallelize([("a",5),("a",6),("b",2)]) rdd.collectAsMap() {'a': 6, 'b': 2} ```

Here, the tuple `("a",6)` has overwritten `("a",5)`.

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