pysparkcli 0.0.8

PySpark Project Buiding Tool

PySpark CLI

This will implement a PySpark Project boiler plate code based on user input.

Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.

PySpark is the Python API for Spark.

Installation Steps:

git clone https://github.com/qburst/PySparkCLI.git

cd PySparkCLI

pip3 install -e . --user

Create a PySpark Project

pysparkcli create [PROJECT_NAME] --master [MASTER_URL] --cores [NUMBER]

master - The URL of the cluster it connects to. You can also use -m instead of --master.
cores - You can also use -c instead of --cores.

Run a PySpark Project

pysparkcli run [PROJECT_NAME]

PySpark Project Test cases

• Running by Project name

pysparkcli test [PROJECT_NAME]

• Running individual test case with filename: test_etl_job.py

pysparkcli test [PROJECT_NAME] -t [etl_job]

FAQ

Common issues while installing pysparkcli:

* pysparkcli: command not found
    Make sure you add user’s local bin to PATH variable.
    Add the following code in .bashrc file

    # set PATH so it includes user's private bin if it exists
    if [ -d "$HOME/.local/bin" ] ; then
        PATH="$HOME/.local/bin:$PATH"
    fi


* JAVA_HOME is not set
    Make sure JAVA_HOME is pointing to your JDK and PYSPARK_PYTHON variable is created.
    You can add them manually by in .bashrc file:

    Example:

        export PYSPARK_PYTHON=python3
        export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64

    Save the file and run the following to update environment.

        source ~/.bashrc

Project Structure

The basic project structure is as follows:

sample
├── __init__.py
├── src
│   ├── app.py
│   ├── configs
│   │   ├── etl_config.json
│   │   └── __init__.py
│   ├── __init__.py
│   ├── jobs
│   │   ├── etl_job.py
│   │   └── __init__.py
│   └── settings
│       ├── default.py
│       ├── __init__.py
│       ├── local.py
│       └── production.py
└── tests
    ├── __init__.py
    ├── test_data
    │   ├── employees
    │   │   └── part-00000-9abf32a3-db43-42e1-9639-363ef11c0d1c-c000.snappy.parquet
    │   └── employees_report
    │       └── part-00000-4a609ba3-0404-48bb-bb22-2fec3e2f1e68-c000.snappy.parquet
    └── test_etl_job.py

8 directories, 15 files

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