Add env python for Spark

.idea/misc.xml

@@ -3,5 +3,5 @@
   <component name="Black">
     <option name="sdkName" value="PySpark" />
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="PySpark_3_10" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (PySpark Training Repository)" project-jdk-type="Python SDK" />
 </project>

.pylintrc

@@ -0,0 +1,3 @@
+[BASIC]
+# Good variable names which should always be accepted, separated by a comma.
+good-names=i, j, k, df

README.md

@@ -1,20 +1,31 @@
-# Python PySpark Training Repository
+Python PySpark Training Repository
+==============
+**Author:** *Yûki VACHOT*
 
-## Installation
+**Updated:** **10/01/24**
-   - [Python 3.10](https://www.python.org/downloads/)
+# CONTENT TABLE
-     - pyspark=3.1.1
-     - findspark
-     - pyspark-test
-   - [Spark 3.1.1](https://spark.apache.org/downloads.html)
-   - [Hadoop 3.3.6](https://hadoop.apache.org/releases.html)
-   - [Java JDK 11](https://www.oracle.com/java/technologies/downloads/#java11)
-   - (not mandatory) [Anaconda for conda](https://www.anaconda.com/download/) 
 
-## Run Python Test
-   - path from src/test_pyspark_training
-   - `pytest -k test_`
 
-## Run pylint for code check
+---
-     
+# Installation
 
-## Run Python doc with Sphinx
+`python -m venv `
+
+- [Python 3.11.7](https://www.python.org/downloads/)
+- [Spark 3.5.0 with Hadoop 3.0.0](https://spark.apache.org/downloads.html)
+- [winutils.exe, .pdb and hadoop.dll](https://github.com/steveloughran/winutils/tree/master/hadoop-3.0.0/bin)
+- [Java JDK 17](https://www.azul.com/downloads/?version=java-17-lts&package=jdk#zulu)
+---
+# Run Python PySpark
+- `python init.py`
+---
+# Run Python Test
+- path from src/test_pyspark_training
+- `pytest -k test_`
+---
+# Run pylint for code check
+
+---
+# Run Python doc with Sphinx
+
+---

init.py

@@ -1,24 +1,21 @@
 import os
-import findspark
+import sys
+from dotenv import load_dotenv
 from pyspark.sql import SparkSession
 from src.pyspark_training.output_dataset_1.compute_output_dataset_1 import compute_output_dataset_1
 
 
-def init_env():
-    os.environ["JAVA_HOME"] = "C:\\Program Files\\Java\\jdk-11"
-    os.environ["SPARK_HOME"] = "C:\\SPARK\\spark-3.1.1-bin-hadoop3.2"
-    os.environ["HADOOP_HOME"] = "C:\\SPARK\\hadoop"
-
-    findspark.init()
-
-
 def init_spark():
     return SparkSession.builder.master("local[*]").getOrCreate()
 
 
 def main():
-    print("hey there")
+    load_dotenv()
-    init_env()
+    print(os.environ["SPARK_HOME"])  # spark-3.5.0-bin-hadoop3
+    print(os.environ["HADOOP_HOME"])  # spark-3.5.0-bin-hadoop3, + winutils et dll hadoop 3.0
+    print(os.environ["JAVA_HOME"])  # java 8 local (zulu)
+    print("EXEC:")
+    print(sys.executable)
     spark_session = init_spark()
 
     compute_output_dataset_1(spark_session)

requirements.txt

@@ -0,0 +1,6 @@
+pyspark
+pyspark-test
+python-dotenv
+pytest
+pylint
+sphinx

spark_check.py

@@ -0,0 +1,27 @@
+from dotenv import load_dotenv
+import sys
+import os
+from pyspark.sql import SparkSession
+
+load_dotenv()
+
+print(os.environ["SPARK_HOME"])
+print(os.environ["HADOOP_HOME"])
+print(os.environ["JAVA_HOME"])
+print("EXEC:")
+print(sys.executable)
+
+spark = SparkSession.builder.getOrCreate()
+df = spark.createDataFrame(
+    [
+        (1, "val1"),
+        (2, "val2"),
+        (3, "val3"),
+        (4, "val4"),
+    ]
+)
+df.show()
+
+df.coalesce(1).write.mode("overwrite").csv("output/testoutput")
+spark.stop()
+print("Done\n")

src/pyspark_training/output_dataset_1/compute_output_dataset_1.py

@@ -1,11 +1,14 @@
+"""
+    This module is used to compute the dataset output_dataset_1.
+"""
 from pyspark.sql import SparkSession
 from pyspark.sql.types import StructType, StructField, IntegerType, StringType
-
 import src.pyspark_training.output_dataset_1.cleaning_output_dataset_1 as C
 import src.pyspark_training.output_dataset_1.processing_output_dataset_1 as P
 
+
 INPUT_DATASET_1_PATH = './assets/output_dataset_1/raw/RAW_input_output_dataset_1.csv'
-OUTPUT_DATASET_1_PATH = './assets/output_dataset_1/output/OUTPUT_output_dataset_1.csv'
+OUTPUT_DATASET_1_PATH = '.\\assets\\output_dataset_1\\output\\OUTPUT_output_dataset_1.csv'
 
 
 def compute_output_dataset_1(spark_session: SparkSession):
@@ -27,4 +30,4 @@ def compute_output_dataset_1(spark_session: SparkSession):
     df = P.add_life_stage(cleaned_df)
 
     df.show()
-    df.write.mode('overwrite').csv(OUTPUT_DATASET_1_PATH)
+    df.coalesce(1).write.mode('overwrite').save(OUTPUT_DATASET_1_PATH, format='csv')

src/test_pyspark_training/conftest.py

@@ -16,7 +16,7 @@ def spark_session(request):
     os.environ['PYSPARK_PYTHON'] = sys.executable
     os.environ['PYSPARK_DRIVER_PYTHON'] = sys.executable
     os.environ["JAVA_HOME"] = "C:\\Program Files\\Java\\jdk-11"
-    os.environ["SPARK_HOME"] = "C:\\SPARK\\spark-3.1.1-bin-hadoop3.2"
+    os.environ["SPARK_HOME"] = "C:\\SPARK\\spark-3.1.1-bin-hadoop3.2\\bin"
     os.environ["HADOOP_HOME"] = "C:\\SPARK\\hadoop"
 
     findspark.init()