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from pyspark.sql import SparkSession | |
spark = SparkSession \ | |
.builder \ | |
.appName("test") \ | |
.getOrCreate() | |
# data is taken from https://github.com/GoogleCloudPlatform/serverless-spark-workshop/blob/main/cell-tower-anomaly-detection/cell-tower-anomaly-detection/01-datasets/telecom_customer_churn_data.csv | |
customer_churn = spark.read.format('csv') \ | |
.option('header','true')\ | |
.option('inferSchema', 'true')\ | |
.load('gs://marifw-datalake-demo/cell-tower-anomaly-detection/telecom_customer_churn/telecom_customer_churn_data.csv') | |
customer_churn.createOrReplaceTempView('customer_churn') | |
res = spark.sql(''' | |
SELECT | |
phones, | |
AVG(hnd_price) AS avg_hnd_price, | |
AVG(totcalls) AS avg_total_calls | |
FROM customer_churn | |
GROUP BY phones | |
''') | |
res.show(truncate=False) |
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