How to preserve milliseconds when converting a date and time string to timestamp using PySpark?
I am trying to convert a column containing date and time as strings to timestamp, however I am losing the milliseconds part during the conversion.
Data
I have a Spark dataframe df that has a date and a time column containing strings. The time string contains milliseconds, as shown below:
+---------+------------+
|date |time |
+---------+------------+
|2018/1/2 |09:53:25.864|
|2018/1/3 |11:32:21.689|
|2018/1/4 |09:34:51.045|
+---------+------------+
What I tried
I concatenated date and time columns to get date_and_time column (string):
import spark.sql.functions as F
df = df.withColumn('date_and_time', F.concat_ws(' ', df.date, df.time))
df.show(3, False)
Output:
+--------+------------+---------------------+
|date |time |date_and_time |
+--------+------------+---------------------+
|2018/1/2|09:53:25.864|2018/1/2 09:53:25.864|
|2018/1/3|11:32:21.689|2018/1/3 11:32:21.689|
|2018/1/4|09:34:51.045|2018/1/4 09:34:51.045|
+--------+------------+---------------------+
Then, I specified the timestamp format using Simple Date Format Date and Time patterns:
timestamp_format = 'yyyy/M/d HH:mm:ss.SSS'
Then, I tried to convert this string to timestamp using a couple of different ways:
df.select(
df.date_and_time,
F.to_timestamp(df.date_and_time, timestamp_format).alias('method_1'),
F.unix_timestamp(df.date_and_time, format=timestamp_format).cast('timestamp').alias('method_2')
).show(3, False)
As you can see below, the timestamp is missing the milliseconds part:
+---------------------+-------------------+-------------------+
|date_and_time |method_1 |method_2 |
+---------------------+-------------------+-------------------+
|2018/1/2 09:53:25.864|2018-01-02 09:53:25|2018-01-02 09:53:25|
|2018/1/3 11:32:21.689|2018-01-03 11:32:21|2018-01-03 11:32:21|
|2018/1/4 09:34:51.045|2018-01-04 09:34:51|2018-01-04 09:34:51|
+---------------------+-------------------+-------------------+
How can I preserve the milliseconds when converting the string to timestamp?
I am using PySpark (Spark: 2.3.1, Python: 3.6.5).
I have looked at previously answered questions on SO and have not found a suitable solution.
python python-3.x apache-spark pyspark timestamp
asked Nov 14 '18 at 16:22
RahulRahul
1469
add a comment |
I am trying to convert a column containing date and time as strings to timestamp, however I am losing the milliseconds part during the conversion.
Data
I have a Spark dataframe df that has a date and a time column containing strings. The time string contains milliseconds, as shown below:
+---------+------------+
|date |time |
+---------+------------+
|2018/1/2 |09:53:25.864|
|2018/1/3 |11:32:21.689|
|2018/1/4 |09:34:51.045|
+---------+------------+
What I tried
I concatenated date and time columns to get date_and_time column (string):
import spark.sql.functions as F
df = df.withColumn('date_and_time', F.concat_ws(' ', df.date, df.time))
df.show(3, False)
Output:
+--------+------------+---------------------+
|date |time |date_and_time |
+--------+------------+---------------------+
|2018/1/2|09:53:25.864|2018/1/2 09:53:25.864|
|2018/1/3|11:32:21.689|2018/1/3 11:32:21.689|
|2018/1/4|09:34:51.045|2018/1/4 09:34:51.045|
+--------+------------+---------------------+
Then, I specified the timestamp format using Simple Date Format Date and Time patterns:
timestamp_format = 'yyyy/M/d HH:mm:ss.SSS'
Then, I tried to convert this string to timestamp using a couple of different ways:
df.select(
df.date_and_time,
F.to_timestamp(df.date_and_time, timestamp_format).alias('method_1'),
F.unix_timestamp(df.date_and_time, format=timestamp_format).cast('timestamp').alias('method_2')
).show(3, False)
As you can see below, the timestamp is missing the milliseconds part:
+---------------------+-------------------+-------------------+
|date_and_time |method_1 |method_2 |
+---------------------+-------------------+-------------------+
|2018/1/2 09:53:25.864|2018-01-02 09:53:25|2018-01-02 09:53:25|
|2018/1/3 11:32:21.689|2018-01-03 11:32:21|2018-01-03 11:32:21|
|2018/1/4 09:34:51.045|2018-01-04 09:34:51|2018-01-04 09:34:51|
+---------------------+-------------------+-------------------+
How can I preserve the milliseconds when converting the string to timestamp?
I am using PySpark (Spark: 2.3.1, Python: 3.6.5).
I have looked at previously answered questions on SO and have not found a suitable solution.
python python-3.x apache-spark pyspark timestamp
asked Nov 14 '18 at 16:22
RahulRahul
1469
add a comment |
I am trying to convert a column containing date and time as strings to timestamp, however I am losing the milliseconds part during the conversion.
Data
I have a Spark dataframe df that has a date and a time column containing strings. The time string contains milliseconds, as shown below:
+---------+------------+
|date |time |
+---------+------------+
|2018/1/2 |09:53:25.864|
|2018/1/3 |11:32:21.689|
|2018/1/4 |09:34:51.045|
+---------+------------+
What I tried
I concatenated date and time columns to get date_and_time column (string):
import spark.sql.functions as F
df = df.withColumn('date_and_time', F.concat_ws(' ', df.date, df.time))
df.show(3, False)
Output:
+--------+------------+---------------------+
|date |time |date_and_time |
+--------+------------+---------------------+
|2018/1/2|09:53:25.864|2018/1/2 09:53:25.864|
|2018/1/3|11:32:21.689|2018/1/3 11:32:21.689|
|2018/1/4|09:34:51.045|2018/1/4 09:34:51.045|
+--------+------------+---------------------+
Then, I specified the timestamp format using Simple Date Format Date and Time patterns:
timestamp_format = 'yyyy/M/d HH:mm:ss.SSS'
Then, I tried to convert this string to timestamp using a couple of different ways:
df.select(
df.date_and_time,
F.to_timestamp(df.date_and_time, timestamp_format).alias('method_1'),
F.unix_timestamp(df.date_and_time, format=timestamp_format).cast('timestamp').alias('method_2')
).show(3, False)
As you can see below, the timestamp is missing the milliseconds part:
+---------------------+-------------------+-------------------+
|date_and_time |method_1 |method_2 |
+---------------------+-------------------+-------------------+
|2018/1/2 09:53:25.864|2018-01-02 09:53:25|2018-01-02 09:53:25|
|2018/1/3 11:32:21.689|2018-01-03 11:32:21|2018-01-03 11:32:21|
|2018/1/4 09:34:51.045|2018-01-04 09:34:51|2018-01-04 09:34:51|
+---------------------+-------------------+-------------------+
How can I preserve the milliseconds when converting the string to timestamp?
I am using PySpark (Spark: 2.3.1, Python: 3.6.5).
I have looked at previously answered questions on SO and have not found a suitable solution.
python python-3.x apache-spark pyspark timestamp
asked Nov 14 '18 at 16:22
RahulRahul
1469
I am trying to convert a column containing date and time as strings to timestamp, however I am losing the milliseconds part during the conversion.
Data
I have a Spark dataframe df that has a date and a time column containing strings. The time string contains milliseconds, as shown below:
+---------+------------+
|date |time |
+---------+------------+
|2018/1/2 |09:53:25.864|
|2018/1/3 |11:32:21.689|
|2018/1/4 |09:34:51.045|
+---------+------------+
What I tried
I concatenated date and time columns to get date_and_time column (string):
import spark.sql.functions as F
df = df.withColumn('date_and_time', F.concat_ws(' ', df.date, df.time))
df.show(3, False)
Output:
+--------+------------+---------------------+
|date |time |date_and_time |
+--------+------------+---------------------+
|2018/1/2|09:53:25.864|2018/1/2 09:53:25.864|
|2018/1/3|11:32:21.689|2018/1/3 11:32:21.689|
|2018/1/4|09:34:51.045|2018/1/4 09:34:51.045|
+--------+------------+---------------------+
Then, I specified the timestamp format using Simple Date Format Date and Time patterns:
timestamp_format = 'yyyy/M/d HH:mm:ss.SSS'
Then, I tried to convert this string to timestamp using a couple of different ways:
df.select(
df.date_and_time,
F.to_timestamp(df.date_and_time, timestamp_format).alias('method_1'),
F.unix_timestamp(df.date_and_time, format=timestamp_format).cast('timestamp').alias('method_2')
).show(3, False)
As you can see below, the timestamp is missing the milliseconds part:
+---------------------+-------------------+-------------------+
|date_and_time |method_1 |method_2 |
+---------------------+-------------------+-------------------+
|2018/1/2 09:53:25.864|2018-01-02 09:53:25|2018-01-02 09:53:25|
|2018/1/3 11:32:21.689|2018-01-03 11:32:21|2018-01-03 11:32:21|
|2018/1/4 09:34:51.045|2018-01-04 09:34:51|2018-01-04 09:34:51|
+---------------------+-------------------+-------------------+
How can I preserve the milliseconds when converting the string to timestamp?
I am using PySpark (Spark: 2.3.1, Python: 3.6.5).
I have looked at previously answered questions on SO and have not found a suitable solution.
python python-3.x apache-spark pyspark timestamp
python python-3.x apache-spark pyspark timestamp
asked Nov 14 '18 at 16:22
RahulRahul
1469
asked Nov 14 '18 at 16:22
RahulRahul
1469
asked Nov 14 '18 at 16:22
RahulRahul
1469
asked Nov 14 '18 at 16:22
RahulRahul
1469
asked Nov 14 '18 at 16:22
RahulRahul
1469
1469
add a comment |
add a comment |
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