timestamp

问题 I searched a lot on Internet but couldn't find the answer. Here is my question: I'm writing some queries in Hive. I have a UTC timestamp and would like to change it to UTC time, e.g., given timestamp 1349049600, I would like to convert it to UTC time which is 2012-10-01 00:00:00. However if I use the built in function from_unixtime(1349049600) in Hive, I get the local PDT time 2012-09-30 17:00:00. I realized there is a built in function called from_utc_timestamp(timestamp, string timezone) .

问题 I have programmed a manual macro in Excel VBA that displays a table to show the history of certain data in a sheet called "evaluation". The data i reference to is in the table "checklist".(Look below) The problem is that the data in "checklist" changes every day or more often. Every time the sheet changes the macro should insert a new row with a new date into the LastRow of the table in "evaluation". (I googled and I found the possibility to use a Timestamp, see below and the function

问题 I am using Spark Dataset and having trouble subtracting days from a timestamp column. I would like to subtract days from Timestamp Column and get new Column with full datetime format. Example: 2017-09-22 13:17:39.900 - 10 ----> 2017-09-12 13:17:39.900 With date_sub functions I am getting 2017-09-12 without 13:17:39.900. 回答1: You cast data to timestamp and expr to subtract an INTERVAL : import org.apache.spark.sql.functions.expr val df = Seq("2017-09-22 13:17:39.900").toDF("timestamp") df

问题 I am using Spark Dataset and having trouble subtracting days from a timestamp column. I would like to subtract days from Timestamp Column and get new Column with full datetime format. Example: 2017-09-22 13:17:39.900 - 10 ----> 2017-09-12 13:17:39.900 With date_sub functions I am getting 2017-09-12 without 13:17:39.900. 回答1: You cast data to timestamp and expr to subtract an INTERVAL : import org.apache.spark.sql.functions.expr val df = Seq("2017-09-22 13:17:39.900").toDF("timestamp") df

问题 I am using Spark Dataset and having trouble subtracting days from a timestamp column. I would like to subtract days from Timestamp Column and get new Column with full datetime format. Example: 2017-09-22 13:17:39.900 - 10 ----> 2017-09-12 13:17:39.900 With date_sub functions I am getting 2017-09-12 without 13:17:39.900. 回答1: You cast data to timestamp and expr to subtract an INTERVAL : import org.apache.spark.sql.functions.expr val df = Seq("2017-09-22 13:17:39.900").toDF("timestamp") df

问题 I have three data types in my database. Datetime, timestamp, and time. I get the time using the date function and tried to insert it into the database under all three columns, but all three columns rejected the A.M, P.M part of the date function. I don't understand why. I need the A.M, P.M part of the date function to be also inserted, so I can sort the data in my database more efficiently by time. Is there another column that can store the A.M, P.M part of the date, or is there a workaround

问题 I have been trying to modify the timestamp when a specific cell is modified in google sheets. My end goal is that if the cell is edited to a value then the modified timestamp reflects and if contents of the cell is entirely deleted, then timestamp also deletes. My current script looks like this: function onEdit() { var s = SpreadsheetApp.getActiveSheet(); if( s.getName() == "Sheet1" ) { var r = s.getActiveCell(); if( r.getColumn() == 4 ) { var nextCell = r.offset(0,1); if((nextCell.getValue()

问题 I currently trying to plot a graph using Jfreechart , and it accept only RegularTimePeriod My date String is: zzz ***Wed Jan 15 10:00:03 +08 2020 From this Question I learned to parse such a string into an OffsetDateTime object. By calling OffsetDateTime I get this string: 2020-01-15T10:00:03+08:00 Then I was trying to make it into RegularTimePeriod , specifically "second". I'm lost and confused about the conversion. Here is my code: TimeSeries s1 = new TimeSeries("Something");

问题 Make is purely timestamp-oriented: if a source is older than its target, the target gets rebuilt. This can cause long recompilations in big applications if one does some major version control detour. Let me give you an example. Suppose I have an old feature branch which didn't get merged yet, and I want to see how it's doing. So starting from master, I would checkout that branch, then merge master into it, then compile. All very fine, and if the feature was small, then differences vs. master

问题 awk can generate a timestamp with strftime function, e.g. $ awk 'BEGIN {print strftime("%Y/%m/%d %H:%M:%S")}' 2019/03/26 08:50:42 But I need a timestamp with fractional seconds, ideally down to nanoseconds. gnu date can do this with the %N element: $ date "+%Y/%m/%d %H:%M:%S.%N" 2019/03/26 08:52:32.753019800 But it is relatively inefficient to invoke date from within awk compared to calling strftime , and I need high performance as I'm processing many large files with awk and need to generate