Map
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Applies a simple 1-to-1 mapping function over each element in the collection.
Examples
In the following examples, we create a pipeline with a PCollection
of produce with their icon, name, and duration.
Then, we apply Map
in multiple ways to transform every element in the PCollection
.
Map
accepts a function that returns a single element for every input element in the PCollection
.
Example 1: Map with a predefined function
We use the function str.strip
which takes a single str
element and outputs a str
.
It strips the input element’s whitespaces, including newlines and tabs.
Example 2: Map with a function
We define a function strip_header_and_newline
which strips any '#'
, ' '
, and '\n'
characters from each element.
Example 3: Map with a lambda function
We can also use lambda functions to simplify Example 2.
Example 4: Map with multiple arguments
You can pass functions with multiple arguments to Map
.
They are passed as additional positional arguments or keyword arguments to the function.
In this example, strip
takes text
and chars
as arguments.
Example 5: MapTuple for key-value pairs
If your PCollection
consists of (key, value)
pairs,
you can use MapTuple
to unpack them into different function arguments.
Example 6: Map with side inputs as singletons
If the PCollection
has a single value, such as the average from another computation,
passing the PCollection
as a singleton accesses that value.
In this example, we pass a PCollection
the value '# \n'
as a singleton.
We then use that value as the characters for the str.strip
method.
Example 7: Map with side inputs as iterators
If the PCollection
has multiple values, pass the PCollection
as an iterator.
This accesses elements lazily as they are needed,
so it is possible to iterate over large PCollection
s that won’t fit into memory.
Note: You can pass the
PCollection
as a list withbeam.pvalue.AsList(pcollection)
, but this requires that all the elements fit into memory.
Example 8: Map with side inputs as dictionaries
If a PCollection
is small enough to fit into memory, then that PCollection
can be passed as a dictionary.
Each element must be a (key, value)
pair.
Note that all the elements of the PCollection
must fit into memory for this.
If the PCollection
won’t fit into memory, use beam.pvalue.AsIter(pcollection)
instead.
Example 9: Map with setup and bundle contexts.
If an expensive shared object, such as a database connection, is required, this can be passed as a bundle or setup context which is invoked like a Python context manager. For example
Related transforms
- FlatMap behaves the same as
Map
, but for each input it may produce zero or more outputs. - Filter is useful if the function is just deciding whether to output an element or not.
- ParDo is the most general elementwise mapping operation, and includes other abilities such as multiple output collections and side-inputs.
Pydoc |
Last updated on 2024/11/08
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