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Version: Java (Groovy)

Time operations cheat sheet

Formats​

hh:mm:ss​

Deephaven time tables use timestamps in the "PTH##M##S##N## format to specify ticking intervals.

result = timeTable(now(), "PT1S")

yyyy-mm-ddT:hh:mm:ss.[millis|micros|nanos] TZ​

Deephaven time tables may also use the yyyy-mm-ddT:hh:mm:ss.[millis|micros|nanos] TZ format to specify a start date.

TZ represents the time zone. A few examples are:

  • UTC
  • ET (New York)
  • JP (Tokyo)
result = timeTable(now(), "PT1S")

Date-time constants​

Deephaven comes with some predefined constants:

  • DAY
  • HOUR
  • MINUTE
  • SECOND
  • WEEK
  • YEAR

These constants all show the time in nanoseconds.

println DAY
println HOUR
println MINUTE
println SECOND
println WEEK
println YEAR_AVG
println YEAR_365

See the Pydoc or Javadoc for further details.

Convert string to Deephaven date-time object​

Deephaven supports converting a string to a Deephaven date-time object via the [parseInstant] method.

Strings should be in the yyyy-mm-ddT:hh:mm:ss.[millis|micros|nanos] TZ format.

dateTimeObject = parseInstant("2021-07-04T08:00:00 ET")
println dateTimeObject.getClass()

Convert nanoseconds to Deephaven date-time object​

Deephaven supports converting a long representing nanoseconds since the Epoch to a Deephaven date-time object via the [autoEpochToInstant] method.

dateTimeObject = epochAutoToInstant(1631045972)

Date-time columns​

Deephaven tables have built-in support for Deephaven date-time objects via the instantCol method.

firstTime = parseInstant("2021-07-04T08:00:00 ET")
secondTime = parseInstant("2021-09-06T12:30:00 ET")
thirdTime = parseInstant("2021-12-25T21:15:00 ET")

result = newTable(
    instantCol("DateTimes", firstTime, secondTime, thirdTime)
)

Timestamp comparison​

Deephaven's filtering has support for timestamp comparisons.

note

Query strings require single quotes ' around timestamps.

firstTime = parseInstant("2021-07-04T08:00:00 UTC")
secondTime = parseInstant("2021-09-06T12:30:00 UTC")
thirdTime = parseInstant("2021-12-25T21:15:00 UTC")

result = newTable(
    instantCol("DateTimes", firstTime, secondTime, thirdTime)
)

filtered = result.where("DateTimes >= '2021-09-06T12:30:00 UTC'")

See our How to use filters guide for more information.

Time zones​

dateTimeObject = parseInstant("2021-07-04T08:00:00 ET")

dayOfMonth = dayOfMonth(dateTimeObject, timeZone("ET"))
println dayOfMonth

Downsampling temporal data via time binning​

Downsampling time series data may be accomplished by calculating binning-intervals for time values and using appropriate aggregation methods, grouped by the binned interval.

dataTable = timeTable("2023-02-06T12:30:09 ET", "P4D")

binnedTable = dataTable.updateView("UpperBin=upperBin(Timestamp, 5 * SECOND)", "LowerBin=lowerBin(Timestamp, 5 * SECOND)")
groupedUpper = binnedTable
    .aggBy([AggFirst("FirstDateTime=Timestamp"),AggLast("LastDateTime=Timestamp")], "UpperBin")

groupedLower = binnedTable
    .aggBy([AggFirst("FirstDateTime=Timestamp"),AggLast("LastDateTime=Timestamp")], "LowerBin")