How to implement Pandas in Apache beam ? I cannot perform left join on multiple columns and Pcollections does not support sql queries. Even the Apache Beam document is not properly framed. I checked but couldn't find any kind of Panda implementation in Apache beam. Can anyone direct me to the desired link ?
pandas is supported in the Dataflow SDK for Python 2. x. As of writing, workers have the pandas v0. 18.1 version pre-installed, so you should not have any issue with that.
Python 3 supportApache Beam 2.14. 0 and higher support Python 3.5, 3.6, and 3.7. We continue to improve the experience for Python 3 users and plan to phase out Python 2 support (BEAM-8371): See details on the Python SDK's Roadmap.
collect function that brings a PCollection or deferred DataFrame into local memory as a pandas DataFrame. After using ib. collect to materialize a deferred DataFrame you will be able to perform any operation in the pandas API, not just those that are supported in Beam.
Pandas uses in-memory computation which makes it ideal for small to medium sized datasets. However, Pandas ability to process big datasets is limited due to out-of-memory errors. A number of alternatives to Pandas are available, one of which is Apache Spark.
There's some confusion going on here.
pandas
is "supported", in the sense that you can use the pandas
library the same way you'd be using it without Apache Beam, and the same way you can use any other library from your Beam pipeline as long as you specify the proper dependencies. It is also "supported" in the sense that it is bundled as a dependency by default so you don't have to specify it yourself. For example, you can write a DoFn
that performs some computation using pandas
for every element; a separate computation for each element, performed by Beam in parallel over all elements.
It is not supported in the sense that Apache Beam currently provides no special integration with it, e.g. you can't use a PCollection
as a pandas dataframe, or vice versa. A PCollection
does not physically contain any data (this should be particularly clear for streaming pipelines) - it is just a placeholder node in Beam's execution plan.
That said, a pandas
-like API for working with Beam PCollections
would certainly be a good idea, and would simplify learning Beam for many existing pandas
users, but I don't think anybody is working on implementing this currently. However, the Beam community is currently discussing the idea of adding schemas to PCollections, which is a step in this direction.
As well as using Pandas directly from DoFns, Beam now has an API to manipulate PCollections as Dataframes. See https://s.apache.org/simpler-python-pipelines-2020 for more details.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With