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 PySpark Documentation
 =====================
 
+.. TODO(SPARK-32204): Add Binder integration at Live Notebook.
+
+PySpark is an interface for Apache Spark in Python. It not only allows you to write
+Spark applications using Python APIs, but also provides the PySpark shell for
+interactively analyzing your data in a distributed environment. PySpark supports most
+of Spark's features such as Spark SQL, DataFrame, Streaming, MLlib
+(Machine Learning) and Spark Core.
+
+.. image:: ../../../docs/img/pyspark-components.png
+  :alt: PySpark Compoenents
+
+**Spark SQL and DataFrame**
+
+Spark SQL is a Spark module for structured data processing. It provides
+a programming abstraction called DataFrame and can also act as distributed
+SQL query engine.
+
+**Streaming**
+
+Running on top of Spark, the streaming feature in Apache Spark enables powerful
+interactive and analytical applications across both streaming and historical data,
+while inheriting Spark’s ease of use and fault tolerance characteristics.
+
+**MLlib**
+
+Built on top of Spark, MLlib is a scalable machine learning library that provides
+a uniform set of high-level APIs that help users create and tune practical machine
+learning pipelines.
+
+**Spark Core**
+
+Spark Core is the underlying general execution engine for the Spark platform that all
+other functionality is built on top of. It provides an RDD (Resilient Distributed Dataset)
+and in-memory computing capabilities.
+
 .. toctree::
     :maxdepth: 2
+    :hidden:
 
     getting_started/index
     user_guide/index