英文:
How to convert string like "yyyy-MM-ddThh:mm:ss+XXXX" to proper date_format in Spark?
问题
我有一列包含字符串数据，类似于"2023-03-13T15:18:14+0700"。我的最终目标是将其转换为正确的日期格式，如"2023-03-13 15:18:14"。最好将时间转换为GMT+7（我的位置），然后删除"T"和"+XXXX"部分。但如果这太难或不可能做到，我只需要删除"T"和"+0700"，因为我的大部分数据都是"+0700"。
我阅读了许多关于SOF的帖子，但到目前为止都没有运气。例如，这里，这里，最接近的是这个，但没有运气，因为它们的格式与我的略有不同。
以下是我从最新帖子中获得的内容：
object test extends App {val spark = SparkSession.builder().master("local[*]").getOrCreate()import spark.implicits._val df = Seq("2023-03-13T15:18:14+0700").toDF("time")val result = df.select(to_timestamp(col("time"), "yyyy-MM-dd'T'hh:mm:ss.SSSXXX").alias("newtime"))result.show(truncate = false) // Nullval result1 = df.select(to_timestamp(col("time"), "yyyy-MM-dd'T'hh:mm:ssXXX").alias("newtime"))result1.show(truncate = false) // Null}
<details><summary>英文:</summary>I have a column containing string data like "**2023-03-13T15:18:14+0700**". My final goal is to convert it to a proper date format like "**2023-03-13 15:18:14**". It's best to convert the time to GMT+7 (my location) and then remove the "T" and "+XXXX" part. But if it's too hard or impossible to do, I just need to remove the "T" and "+0700" since most of my data is "+0700".I read many posts on SOF but had no luck so far. For example, [here][1], [here][2], and the closest one is [this][3] but no luck since their format is a bit different from mine.Below is what I got from the latest post:object test extends App {val spark = SparkSession.builder().master("local[*]").getOrCreate()import spark.implicits._val df = Seq("2023-03-13T15:18:14+0700").toDF("time")val result = df.select(to_timestamp(col("time"), "yyyy-MM-dd'T'hh:mm:ss.SSSXXX").alias("newtime"))result.show(truncate = false) // Nullval result1 = df.select(to_timestamp(col("time"), "yyyy-MM-dd'T'hh:mm:ssXXX").alias("newtime"))result1.show(truncate = false) // Null}[1]: https://stackoverflow.com/questions/70394354/why-i-cant-parse-this-date-format-yyyy-mm-ddthhmmss-sssz[2]: https://stackoverflow.com/questions/60857315/how-to-handle-t-and-z-in-the-date-format-using-pyspark-functions[3]: https://stackoverflow.com/questions/54690305/spark-javahow-to-convert-dataset-string-column-of-format-yyyy-mm-ddthhmmss-s</details># 答案1**得分**: 1使用 ```cast()``` 转换
from pyspark.sql.functions import col
from pyspark.sql.types import TimestampType
df = df.withColumn("time", col("time").cast(TimestampType()))
df.show()
***输出***
+-------------------+
| time|
+-------------------+
|2023-03-13 08:18:14|
+-------------------+
***模式***
root
|-- time: timestamp (nullable = true)
<details><summary>英文:</summary>Use ```cast()``` transformation
from pyspark.sql.functions import col
from pyspark.sql.types import TimestampType
df = df.withColumn("time", col("time").cast(TimestampType()))
df.show()
***Output***
+-------------------+
| time|
+-------------------+
|2023-03-13 08:18:14|
+-------------------+
***Schema***
root
|-- time: timestamp (nullable = true)
</details># 答案2**得分**: 1您没有使用正确的格式，您提供的日期是ISO 8601类型的，正确的格式是 `yyyy-MM-dd'T'HH:mm:ssZ`，以下是如何使用 `to_timestamp` 函数来进行转换：```pythonspark = SparkSession.builder.master("local[*]").getOrCreate()df = spark.createDataFrame([["2023-03-13T15:18:14+0700"]], ['time'])df = df.withColumn("timestamp_utc", to_timestamp("time", "yyyy-MM-dd'T'HH:mm:ssZ"))df.show(truncate=False)df.printSchema()
输出如下：
+------------------------+-------------------+|time |timestamp_utc |+------------------------+-------------------+|2023-03-13T15:18:14+0700|2023-03-13 09:18:14|+------------------------+-------------------+root|-- time: string (nullable = true)|-- timestamp_utc: timestamp (nullable = true)
英文:
You are not using the right format, the date you have is of type ISO 8601, the right format is yyyy-MM-dd'T'HH:mm:ssZ, here's how to use it using to_timestamp function:
spark = SparkSession.builder.master("local[*]").getOrCreate()df = spark.createDataFrame([["2023-03-13T15:18:14+0700"]], ['time'])df = df.withColumn("timestamp_utc", to_timestamp("time", "yyyy-MM-dd'T'HH:mm:ssZ"))df.show(truncate=False)df.printSchema()+------------------------+-------------------+|time |timestamp_utc |+------------------------+-------------------+|2023-03-13T15:18:14+0700|2023-03-13 09:18:14|+------------------------+-------------------+root|-- time: string (nullable = true)|-- timestamp_utc: timestamp (nullable = true)
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