在pyspark数据框中的两个日期之间生成每月时间戳记 [英] Generating monthly timestamps between two dates in pyspark dataframe

问题描述

我有一些带有"date"列的DataFrame，并且我试图从"date"列中生成一个在最小和最大日期之间的所有每月时间戳记的新DataFrame.

I have some DataFrame with "date" column and I'm trying to generate a new DataFrame with all monthly timestamps between the min and max date from the "date" column.

解决方案之一如下:

month_step = 31*60*60*24

min_date, max_date = df.select(min_("date").cast("long"), max_("date").cast("long")).first()

df_ts = spark.range(
    (min_date / month_step) * month_step, 
    ((max_date / month_step) + 1) * month_step,
    month_step
).select(col("id").cast("timestamp").alias("yearmonth"))

df_formatted_ts = df_ts.withColumn(
    "yearmonth",
    f.concat(f.year("yearmonth"), f.lit('-'), format_string("%02d", f.month("yearmonth")))
).select('yearmonth')

df_formatted_ts.orderBy(asc('yearmonth')).show(150, False)

问题在于我将month_step视为31天，但这并不正确，因为某些月份中有30天甚至28天.可以通过某种方式使其更加精确吗?

The problem is that I took as a month_step 31 days and its not really correct because some of the months have 30 days and even 28 days. Is possible to somehow make it more precise?

请注意:稍后，我只需要 year 和 month 值，因此我将忽略日期和时间.但是无论如何，因为我正在生成一个很大的日期范围(2001年至2018年)之间的时间戳，所以时间戳发生了变化.

Just as a note: Later I only need year and month values so I will ignore day and time. But anyway because I'm generating timestamps between quite a big date range (between 2001 and 2018) the timestamps shifting.

这就是为什么有时会跳过几个月的原因.例如，此快照缺少2010-02:

That's why sometimes some months will be skipped. For example, this snapshot is missing 2010-02:

|2010-01  |
|2010-03  |
|2010-04  |
|2010-05  |
|2010-06  |
|2010-07  |

我检查了一下，从2001年到2018年仅跳过了3个月.

I checked and there are just 3 months which were skipped from 2001 through 2018.

推荐答案

假设您具有以下DataFrame:

Suppose you had the following DataFrame:

data = [("2000-01-01","2002-12-01")]
df = spark.createDataFrame(data, ["minDate", "maxDate"])
df.show()
#+----------+----------+
#|   minDate|   maxDate|
#+----------+----------+
#|2000-01-01|2002-12-01|
#+----------+----------+

您可以按照与/a>.

只需将pyspark.sql.functions.datediff替换为pyspark.sql.functions.months_between，然后使用add_months而不是date_add:

Just replace pyspark.sql.functions.datediff with pyspark.sql.functions.months_between, and use add_months instead of date_add:

import pyspark.sql.functions as f

df.withColumn("monthsDiff", f.months_between("maxDate", "minDate"))\
    .withColumn("repeat", f.expr("split(repeat(',', monthsDiff), ',')"))\
    .select("*", f.posexplode("repeat").alias("date", "val"))\
    .withColumn("date", f.expr("add_months(minDate, date)"))\
    .select('date')\
    .show(n=50)
#+----------+
#|      date|
#+----------+
#|2000-01-01|
#|2000-02-01|
#|2000-03-01|
#|2000-04-01|
# ...skipping some rows...
#|2002-10-01|
#|2002-11-01|
#|2002-12-01|
#+----------+

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