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[FSTORE-1008] enable interacting with java client to hopsworks #344

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[FSTORE-1008] enable interacting with java client to hopsworks #344

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9 changes: 7 additions & 2 deletions docs/user_guides/fs/compute_engines.md
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Expand Up @@ -4,12 +4,12 @@ In order to execute a feature pipeline to write to the Feature Store, as well as
Hopsworks Feature Store APIs are built around dataframes, that means feature data is inserted into the Feature Store from a Dataframe and likewise when reading data from the Feature Store, it is returned
as a Dataframe.

As such, Hopsworks supports three computational engines:
As such, Hopsworks supports four computational engines:

1. [Apache Spark](https://spark.apache.org): Spark Dataframes and Spark Structured Streaming Dataframes are supported, both from Python environments (PySpark) and from Scala environments.
2. [Pandas](https://pandas.pydata.org/): For pure Python environments without dependencies on Spark, Hopsworks supports [Pandas Dataframes](https://pandas.pydata.org/).
3. [Apache Flink](https://flink.apache.org): Flink Data Streams are currently supported as an experimental feature from Java/Scala environments.
3. [Apache Beam](https://beam.apache.org/) *experimental*: Beam Data Streams are currently supported as an experimental feature from Java/Scala environments.
4. [Apache Beam](https://beam.apache.org/) *experimental*: Beam Data Streams are currently supported as an experimental feature from Java/Scala environments.

Hopsworks supports running [compute on the platform itself](../../concepts/dev/inside.md) in the form of [Jobs](../projects/jobs/pyspark_job.md) or in [Jupyter Notebooks](../projects/jupyter/python_notebook.md).
Alternatlively, you can also connect to Hopsworks using Python or Spark from [external environments](../../concepts/dev/outside.md), given that there is network connectivity.
Expand Down Expand Up @@ -76,3 +76,8 @@ Apache Beam integration with Hopsworks feature store was only tested using Dataf

For more details head over to the [Getting Started Guide](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/integrations/java/beam).

## Java
It is also possible to interact to Hopsworks feature store using pure Java environments without dependencies on Spark, Flink or Beam.
However, this is limited to retrieval of feature vector(s) from the online Feature Store.

For more details head over to the [Getting Started Guide](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/java).
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