PySpark: How to Extract Hour from Timestamp

You can use the following methods to extract the hour from a timestamp in PySpark:

Method 1: Extract Hour from Timestamp

from pyspark.sql import functions as F

df_new = df.withColumn('hour', F.hour(df['ts']))

If the timestamp is 2023-01-15 04:14:22 then this syntax would return 4.

Method 2: Extract Timestamp Truncated to Hour

from pyspark.sql import functions as F

df_new = df.withColumn('hour', F.date_trunc('hour', df['ts']))

If the timestamp is 2023-01-15 04:14:22 then this syntax would return 2023-01-15 04:00:00.

The following example shows how to use each method in practice with the following PySpark DataFrame that contains information about sales made on various timestamps at some company:

from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()

from pyspark.sql import functions as F

#define data
data = [['2023-01-15 04:14:22', 225],
        ['2023-02-24 10:55:01', 260],
        ['2023-07-14 18:34:59', 413],
        ['2023-10-30 22:20:05', 368]] 
  
#define column names
columns = ['ts', 'sales'] 
  
#create dataframe using data and column names
df = spark.createDataFrame(data, columns)

#convert string column to timestamp
df = df.withColumn('ts', F.to_timestamp('ts', 'yyyy-MM-dd HH:mm:ss'))
  
#view dataframe
df.show()

+-------------------+-----+
|                 ts|sales|
+-------------------+-----+
|2023-01-15 04:14:22|  225|
|2023-02-24 10:55:01|  260|
|2023-07-14 18:34:59|  413|
|2023-10-30 22:20:05|  368|
+-------------------+-----+

Example 1: Extract Hour from Timestamp

We can use the following syntax to extract only the hour from each timestamp in the ts column of the DataFrame:

from pyspark.sql import functions as F

#extract hour from each timestamp in 'ts' column
df_new = df.withColumn('hour', F.hour(df['ts']))

#view new DataFrame
df_new.show()

+-------------------+-----+----+
|                 ts|sales|hour|
+-------------------+-----+----+
|2023-01-15 04:14:22|  225|   4|
|2023-02-24 10:55:01|  260|  10|
|2023-07-14 18:34:59|  413|  18|
|2023-10-30 22:20:05|  368|  22|
+-------------------+-----+----+

The new hour column shows only the hour from each timestamp in the ts column.

Example 2: Extract Timestamp Truncated to Hour

We can use the following syntax to return each timestamp from the ts column truncated to the hour:

from pyspark.sql import functions as F

#create new column that contains timestamp truncated to the hour
df_new = df.withColumn('hour', F.date_trunc('hour', df['ts']))

#view new DataFrame
df_new.show()

+-------------------+-----+-------------------+
|                 ts|sales|               hour|
+-------------------+-----+-------------------+
|2023-01-15 04:14:22|  225|2023-01-15 04:00:00|
|2023-02-24 10:55:01|  260|2023-02-24 10:00:00|
|2023-07-14 18:34:59|  413|2023-07-14 18:00:00|
|2023-10-30 22:20:05|  368|2023-10-30 22:00:00|
+-------------------+-----+-------------------+

The new hour column shows each timestamp from the ts column truncated to the hour.