Spark job stuck on one task only - apache-spark

Question

I have setup Spark 3.x with Hadoop 3.x with YARN. I have to simply index some data using distributed data pipeline i.e., via Spark. Following is the code snippet that I have used for spark app (pyspark)
def index_module(row ):
pass
def start_job(DATABASE_PATH):
global SOLR_URI
warehouse_location = abspath('spark-warehouse')
spark = SparkSession \
.builder \
.appName("Python Spark SQL Hive integration example") \
.config("spark.sql.warehouse.dir", warehouse_location) \
.enableHiveSupport() \
.getOrCreate()
solr_client = pysolr.Solr(SOLR_URI)
df = spark.read.format("csv").option("quote", "\"").option("escape", "\\").option("header", "true").option(
"inferSchema", "true").load(DATABASE_PATH)
df.createOrReplaceTempView("abc")
df2 = spark.sql("select * from abc")
df2.toJSON().map(index_module).collect()
solr_client.commit()
if __name__ == '__main__':
try:
DATABASE_PATH = sys.argv[1].strip()
except:
print("Input file missing !!!", file=sys.stderr)
sys.exit()
start_job(DATABASE_PATH)
There are about 120 csv files and 200 Million records. Each of it should be indexed idealy. To run the job on YARN, I have run following command (according to my Hadoop resources)
spark-submit --class org.apache.spark.examples.SparkPi --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 2g --num-executors 5 --executor-cores 1 /PATH/myscript.py
Now, about 3 days has been passed. My job is running. Following are the status of executors as shown from YARN dashboard
As shown in the figures, for each executor, all tasks are completed, just one left. Why it is so ? It should also be completed. What is the problem with above all ? What should be the possible way to fix the issue ?