my date which is in below format
"_messagetime" => "08/08/2022 22:18:17.254 +0530"
I am using date filter in my logstash
date {
match => ["_messagetime", "YYYY-MM-dd HH:mm:ss.SSS"]
}
but I am getting
"_dateparsefailure"
Can anyone plz suggest what might be wrong with my approach
The date filter must match the entire value of the field. It cannot just parse a prefix. Also, your date filter has YYYY-MM-dd, but your field has dd/MM/YYYY.
You can parse that field using
date { match => ["_messagetime", "dd/MM/YYYY HH:mm:ss.SSS Z"] }
to get "#timestamp" => 2022-08-08T16:48:17.254Z. Note the trailing Z in the value of [#timestamp] -- all timestamps in logstash are stored in Zulu / UTC timezone.
your error it's caused by the " +0530" string in the _messagetime field content.
To fix this, one option is :
Remove this string before the date plugin, you can do this with use of grok or dissect
For example :
filter {
grok {
match => { "_messagetime" => "%{DATESTAMP:newdate}%{DATA:trash}" }
}
}
Apply the same date plugin conf wich must work on new content now without " +0530" occurence
Related
I have date field like this 1994/Jan In CSV .How to change it into date format.
What i am trying is this :
filter {mutate{convert=>["field_name","date"]}}
But its not working
Try this :
filter{
date{
match => [ "field_source","yyyy/MMM"]
target => "field_target"
}
}
Introduction:
In Azure Data Explorer there is a make-series-Operator which allow us to create series of specified aggregated values along specified axis.
Where is the problem:
The operator works good except the changes in timestamp format.
For example
let resolution = 1d;
let timeframe = 3d;
let start_ts = datetime_add('second', offset, ago(timeframe));
let end_ts = datetime_add('second', offset, now());
Table
| make-series max(value) default=0 on timestamp from start_ts to end_ts step resolution by col_1, col_2
Current results:
I got the result contains the timestamp in UTC like the following
"max_value": [
-2.69,
-2.79,
-2.69
],
"timestamp": [
"2020-03-29T18:01:08.0552135Z",
"2020-03-30T18:01:08.0552135Z",
"2020-03-31T18:01:08.0552135Z"
],
Expected result:
result should be like the following
"max_value": [
-2.69,
-2.79,
-2.69
],
"timestamp": [
"2020-03-29 18:01:08",
"2020-03-30 18:01:08",
"2020-03-31 18:01:08"
],
Question:
is there any way to change the datetime format which generated in make-series operation in kusto to be NOT in UTC format.
is there any way to change the datetime format which generated in make-series operation in kusto to be NOT in UTC format.
it's not clear what you define as "UTC Format". Kusto/ADX uses the ISO 8601 standard, and timestamps are always UTC. You can see that is used in your original message, e.g. 2020-03-29T18:01:08.0552135Z.
if, for whatever reason, you want to present datetime values in a different format, inside of a dynamic column (array or property bag), you could achieve that using mv-apply and format_datetime():
print arr = dynamic(
[
"2020-03-29T18:01:08.0552135Z",
"2020-03-30T18:01:08.0552135Z",
"2020-03-31T18:01:08.0552135Z"
])
| mv-apply arr on (
summarize make_list(format_datetime(todatetime(arr), "yyyy-MM-dd HH:mm:ss"))
)
How to compare date in logstash. I want to compare date with a constant date value. The below code fails in Logstash with ruby exception.
if [start_dt] <= "2016-12-31T23:23:59.999Z"
I finally figured it out. First convert the constant date from string to date using logstash date plugin. Then you can compare this date with your date field.
mutate{
add_field => { "str_dt" => "2016-12-31T23:23:59.999Z"}
}
date {
match => ["str_dt", "YYYY-MM-dd'T'HH:mm:ss.SSSZ"]
target => "constant_date"
}
if [start_dt] <= [constant_date] {
}
If a date literal is used in a pushed-down filter expression, e.g.
val postingDate = java.sql.Date.valueOf("2016-06-03")
val count = jdbcDF.filter($"POSTINGDATE" === postingDate).count
where the POSTINGDATE column is of JDBC type Date, the resulting pushed-down SQL query looks like the following:
SELECT .. <columns> ... FROM <table> WHERE POSTINGDATE = '2016-06-03'
Specifically, the date is compiled into a string literal using the hardcoded yyyy-MM-dd format that java.sql.Date.toString emits. Note the implied string conversion for date (and timestamp) values in JDBCRDD.compileValue
/**
* Converts value to SQL expression.
*/
private def compileValue(value: Any): Any = value match {
case stringValue: String => s"'${escapeSql(stringValue)}'"
case timestampValue: Timestamp => "'" + timestampValue + "'"
case dateValue: Date => "'" + dateValue + "'"
case arrayValue: Array[Any] => arrayValue.map(compileValue).mkString(", ")
case _ => value
}
The resulting query fails if the database is expecting a different format for date string literals. For example, the default format for Oracle is 'dd-MMM-yy', so when the relation query is executed, it fails with a syntax error.
ORA-01861: literal does not match format string
01861. 00000 - "literal does not match format string"
In some situations it may be possible to change the database's expected date format to match the Java format, but in our case we don't have control over that.
It seems like this kind of conversion ought to be going through some kind of vendor specific translation (e.g. through a JDBCDialect). I've filed a JIRA issue to that effect, but, meanwhile, I suggestions how to work around this? I've tried a variety of different approaches, both on the spark side and the JDBC side, but haven't come up with anything yet. This is a critical issue for us, as we're processing very large tables organized by date -- without pushdown, we end up pulling over the entire table for a Spark-side filter.
I have a csv file which store up cpu usage. There is a field with date format like this "20150101-00:15:00". How can I change it to #timestamp in logstash as shown in kibana?
Use date filter on that field:
date {
match => [ "dateField" , "yyyyMMdd-HH:mm:ss"]
}
It will add the #timestamp field.
See documentation here: https://www.elastic.co/guide/en/logstash/current/plugins-filters-date.html