Here is the cheat sheet I used for myself when writing those codes. Import most of the sql functions and types – import pyspark from pyspark.sql import functions as F from pyspark.sql import Window from pyspark.sql.functions import col, udf, explode, array, lit, concat, desc, substringindex from pyspark.sql.types import IntegerType. This PySpark SQL cheat sheet is designed for those who have already started learning about and using Spark and PySpark SQL. If you are one among them, then this sheet will be a handy reference for you. However, don’t worry if you are a beginner and have no idea about how PySpark SQL works.
Let’s configure pyspark in PyCharm in Ubuntu.
First, download spark from the source. http://spark.apache.org/downloads.html
There is a simple two step process for the configuration.
First, setup spark home, SPARK_HOME, in the ‘etc/environment’
SPARK_HOME=location-to-downloaded-spark-folder
Here, in my case, the location of downloaded spark is /home/pujan/Softwares/spark-2.0.0-bin-hadoop2.7
And, do remember to restart your system to reload the environment variables.
Second, in the pycharm IDE, in the project in which you want to configure pyspark, open Settings, File -> Settings.
Then, in the project section, click on “Project Structure”.
We need to add two files, one py4j-0.10.1-src.zip, another pyspark.zip, in the ‘Content Root’ of ‘Project Structure’
In my case, the project’s name is Katyayani, so, in the menu, Settings -> Project: Katyayani -> Project Structure . On the right side, click on ‘Add Content Root’ and add ‘py4j-0.10.1-src.zip’ [/home/pujan/Softwares/spark-2.0.0-bin-hadoop2.7/python/lib/py4j-0.10.1-src.zip] and ‘pyspark.zip'[/home/pujan/Softwares/spark-2.0.0-bin-hadoop2.7/python/lib/pyspark.zip]
After this configuration, lets test our configuration that we can access spark from pyspark. For this, write a python script in pycharm. The following screenshot shows a very simple python script and the log message of successful interaction with spark.
And, this concludes our successful configuration of pyspark in pycharm.
Let’s configure pyspark in PyCharm in Ubuntu.
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First, download spark from the source. http://spark.apache.org/downloads.html
There is a simple two step process for the configuration.
First, setup spark home, SPARK_HOME, in the ‘etc/environment’
SPARK_HOME=location-to-downloaded-spark-folder
Here, in my case, the location of downloaded spark is /home/pujan/Softwares/spark-2.0.0-bin-hadoop2.7
And, do remember to restart your system to reload the environment variables.
Second, in the pycharm IDE, in the project in which you want to configure pyspark, open Settings, File -> Settings.
Then, in the project section, click on “Project Structure”.
We need to add two files, one py4j-0.10.1-src.zip, another pyspark.zip, in the ‘Content Root’ of ‘Project Structure’
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In my case, the project’s name is Katyayani, so, in the menu, Settings -> Project: Katyayani -> Project Structure . On the right side, click on ‘Add Content Root’ and add ‘py4j-0.10.1-src.zip’ [/home/pujan/Softwares/spark-2.0.0-bin-hadoop2.7/python/lib/py4j-0.10.1-src.zip] and ‘pyspark.zip'[/home/pujan/Softwares/spark-2.0.0-bin-hadoop2.7/python/lib/pyspark.zip]
After this configuration, lets test our configuration that we can access spark from pyspark. For this, write a python script in pycharm. The following screenshot shows a very simple python script and the log message of successful interaction with spark.
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And, this concludes our successful configuration of pyspark in pycharm.