In Spark's WebUI (port 8080) and on the environment tab there is a setting of the below:
user.timezone Zulu
Do you know how/where I can override this to UTC?
Env details:
(GMT-5:00) Eastern Time (US & Canada)Add the local time offset to the UTC time. For example, if your local time offset is -5:00, and if the UTC time is shown as 11:00, add -5 to 11. The time setting when adjusted for offset is 06:00 (6:00 A.M.). Note The date also follows UTC format.
The ID of session local timezone in the format of either region-based zone IDs or zone offsets. Region IDs must have the form 'area/city', such as 'America/Los_Angeles'. Zone offsets must be in the format ' (+|-)HH ', ' (+|-)HH:mm ' or ' (+|-)HH:mm:ss ', e.g '-08', '+01:00' or '-13:33:33'.
pyspark.sql.functions.from_utc_timestamp(timestamp, tz) So in Spark this function just shift the timestamp value from UTC timezone to the given timezone. This function may return confusing result if the input is a string with timezone, e.g. '2018-03-13T06:18:23+00:00'.
You can set it in the cluster -> configuration -> Advanced Option -> spark, set the spark parameter: spark. sql. session. timeZone Hongkong.
Now you can use:
spark.conf.set("spark.sql.session.timeZone", "UTC")
Since https://issues.apache.org/jira/browse/SPARK-18936 in 2.2.0
Additionally, I set my default TimeZone to UTC to avoid implicit conversions
TimeZone.setDefault(TimeZone.getTimeZone("UTC"))
Otherwise you will get implicit conversions from your default Timezone to UTC when no Timezone information is present in the Timestamp you're converting
Example:
val rawJson = """ {"some_date_field": "2018-09-14 16:05:37"} """
val dsRaw = sparkJob.spark.createDataset(Seq(rawJson))
val output =
dsRaw
.select(
from_json(
col("value"),
new StructType(
Array(
StructField("some_date_field", DataTypes.TimestampType)
)
)
).as("parsed")
).select("parsed.*")
If my default TimeZone is Europe/Dublin which is GMT+1 and Spark sql session timezone is set to UTC, Spark will assume that "2018-09-14 16:05:37" is in Europe/Dublin TimeZone and do a conversion (result will be "2018-09-14 15:05:37")
In some cases you will also want to set the JVM timezone. For example, when loading data into a TimestampType column, it will interpret the string in the local JVM timezone. To set the JVM timezone you will need to add extra JVM options for the driver and executor:
spark = pyspark.sql.SparkSession \
.Builder()\
.appName('test') \
.master('local') \
.config('spark.driver.extraJavaOptions', '-Duser.timezone=GMT') \
.config('spark.executor.extraJavaOptions', '-Duser.timezone=GMT') \
.config('spark.sql.session.timeZone', 'UTC') \
.getOrCreate()
We do this in our local unit test environment, since our local time is not GMT.
Useful reference: https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
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