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## Install
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```sh
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pip install managed_spark_connect
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pip install google-cloud-managed-spark-connect
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```
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## Uninstall
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```sh
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pip uninstall managed_spark_connect
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pip uninstall google-cloud-managed-spark-connect
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```
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## Setup
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1. Install the latest version of Managed Spark Connect:
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```sh
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pip install -U managed-spark-connect
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pip install -U google-cloud-managed-spark-connect
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```
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2. Add the required imports into your PySpark application or notebook and start
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**Installation**: To use magic commands, install the required dependencies manually:
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```bash
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pip install managed-spark-connect
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pip install google-cloud-managed-spark-connect
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pip install IPython sparksql-magic
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```
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**Note**: Magic commands are optional. If you only need basic ManagedSparkSession functionality without Jupyter magic support, install only the base package:
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```bash
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pip install managed-spark-connect
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pip install google-cloud-managed-spark-connect
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```
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## Migrating from dataproc-spark-connect
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The `dataproc-spark-connect` package and the `google.cloud.dataproc_spark_connect` module have been renamed to `managed-spark-connect` / `google.cloud.managed_spark_connect`, and `DataprocSparkSession` has been renamed to `ManagedSparkSession`. The old import path and class name still work but emit a `DeprecationWarning` — update your imports when convenient:
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The `dataproc-spark-connect` package and the `google.cloud.dataproc_spark_connect` module have been renamed to `google-cloud-managed-spark-connect` / `google.cloud.managed_spark_connect`, and `DataprocSparkSession` has been renamed to `ManagedSparkSession`. The old import path and class name still work but emit a `DeprecationWarning` — update your imports when convenient:
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