failed to parse csv specific date format into date in logstash - logstash

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"
}
}

Related

"_dateparsefailure" while parsing date using date in logstash

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

junk data fix in pyspark or linux command

I have large data set will come from NIFI, then I'll do ETL transformation with pyspark,
unfortunately, one column in middle got split with new line, making extra column and existing records as NULL for same row, So I need to fix with Linux command at Nifi flow or pyspark code while doing ETL transformation
Ex: source.csv
1,hi,21.0,final,splitexthere,done,v1,v2,done
2,hi,21.0,final,splitext
here,done,v1,v2,done
3,hi,21.0,final,splitexthere,done,v1,v2,done
4,hi,21.0,final,splitexthere,done,v1,v2,failed
expected.csv
1,hi,21.0,final,splitexthere,done,v1,v2,done
2,hi,21.0,final,splitexthere,done,v1,v2,done
3,hi,21.0,final,splitexthere,done,v1,v2,done
4,hi,21.0,final,splitexthere,done,v1,v2,failed
here are some inputs,
we don't know which column will be split like above splittexhere
id column will be numbers always
and one file has multiple splits with new line

As #daggett highlighted, data must conform to the CSV format specifications to be valid across heterogeneous systems.
Add a ValidateRecord or ConvertRecord processor to your NiFi flow to validate CSV to CSV. This will filter out invalid records and valid records from the source data, so basically two forks out of a flowfile and then you can have a separate logic to handle/clean invalid data. Same can be doable in Spark as well but in NiFi it is pretty straightforward!
Note: While configuring CSVReader schema, make sure that all the fields are NOT NULL.
eg. Sample schema for two fields (you have nine fields)
{
"type" : "record",
"namespace" : "com.example.etl",
"name" : "validate_csv_data",
"fields" : [
{ "name" : "col_1", "type" : "string" },
{ "name" : "col_2", "type" : "string" }
]
}

Change datetime format generated with make-series operation in Kusto

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

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] {
}

Change field to timestamp

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

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