如何在pyspark中以纳秒为单位将字符串转换为时间戳

问题描述

我正在处理时间戳包含纳秒的数据，并试图将字符串转换为时间戳格式.

I am working with data with timestamps that contain nanoseconds and am trying to convert the string to timestamp format.

时间"列如下所示:

+---------------+
|      Time     |
+---------------+
|091940731349000|
|092955002327000|
|092955004088000|
+---------------+

我想将其转换为:

+------------------+
|    Timestamp     |
+------------------+
|09:19:40.731349000|
|09:29:55.002327000|
|09:29:55.004088000|
+------------------+

根据我在网上找到的内容，我不需要使用 udf 来执行此操作，并且应该有一个可以使用的本机函数.

From what I have found online, I don't need to use a udf to do this and there should be a native function that I can use.

我尝试了 cast 和 to_timestamp 但得到了 'null' 值:

I have tried cast and to_timestamp but got 'null' values:

df_new = df.withColumn('Timestamp', df.Time.cast("timestamp"))
df_new.select('Timestamp').show()

+---------+
|Timestamp|
+---------+
|     null|
|     null|
+---------+

推荐答案

你的代码有两个问题:

• 输入不是有效的时间戳表示.
• Spark 不提供可以表示没有日期组件的时间的类型

最接近所需输出的是将输入转换为符合 JDBC 的 java.sql.Timestamp 格式:

The closest you can get to the required output is to convert input to JDBC compliant java.sql.Timestamp format:

from pyspark.sql.functions import col, regexp_replace

df = spark.createDataFrame(
    ["091940731349000", "092955002327000", "092955004088000"],
    "string"
).toDF("time")

df.select(regexp_replace(
  col("time"),
  "^(\\d{2})(\\d{2})(\\d{2})(\\d{9}).*",
  "1970-01-01 $1:$2:$3.$4"
).cast("timestamp").alias("time")).show(truncate = False)

# +--------------------------+
# |time                      |
# +--------------------------+
# |1970-01-01 09:19:40.731349|
# |1970-01-01 09:29:55.002327|
# |1970-01-01 09:29:55.004088|
# +--------------------------+

如果你只想要一个字符串跳过转换并将输出限制为:

If you want just a string skip cast and limit output to:

df.select(regexp_replace(
  col("time"),
  "^(\\d{2})(\\d{2})(\\d{2})(\\d{9}).*",
  "$1:$2:$3.$4"
).alias("time")).show(truncate = False)

# +------------------+
# |time              |
# +------------------+
# |09:19:40.731349000|
# |09:29:55.002327000|
# |09:29:55.004088000|
# +------------------+

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