Splunk Search

Subtracting time differences - inconsistency in strptime results?

sdevadas
Path Finder

I have a set of events which are of the type:
Type=httpPreReply Guid=b6d4d009-4643-4ff2-8fad-e20868ce3a17 Datetime=07/08/201118:59:59.565

(this is in the message field of windows event log).

Datetime is some application timing field.

I extract related pairs of Datetime fields using transaction (i.e. Guid) and convert them using strptime and then calculate their difference.

  1. The datetime fields are extracted correctly
  2. For some reason strptime works for the first few hundred results and then start behaving inconsistently i.e. only one of the Datetime fields are converted, or sometimes both are not.
  3. Due to this I am unable to get differences of pairs of time correctly.

Would anyone know why Datetime strings convert inconsistently somewhere in the middle of the result set (they are all generated from the same source). Any hints on debugging would also be appreciated.

My query is:

earliest="07/08/2011:19:00:00" latest="07/08/2011:20:00:00" host="PRWBHZ*" Type="Information" SourceName="Horizon" (Message="Type=httpPostSend*" OR Message="Type=httpPreReply*") | rex field=Message "Type=(?<TheType>.*) Guid=(?<TheGuid>.*) Datetime=(?<TheDatetime>.*).*" | transaction TheGuid | eval TheDatetimeCount=mvcount(TheDatetime) | search TheDatetimeCount=2 | eval firstdtimestr=mvindex(TheDatetime, 0) | eval secondtimestr=mvindex(TheDatetime, 1)  | eval firsttime=strptime(firsttimestr, "%m/%d/%Y%H:%M:%S.%z") | eval secondtime=strptime(secondtimestr, "%m/%d/%Y%H:%M:%S.%z") | eval TotalTime=firsttime - secondtime | table firsttimestr, secondtimestr, firsttime, secondtime, TotalTime

The results come back as correctly for the first few hundred results:
| firsttimestr | secondtimestr | firsttime | secondtime |TotalTime

2 | 07/08/201118:27:06.453 | 07/08/201118:27:06.500 | 1310132046.000000 | 1310131626.000000 | 420.000000

3 | 07/08/201118:07:51.353 | 07/08/201118:07:51.400 | 1310134491.000000 | 1310134071.000000 | 420.000000

4 | 07/08/201118:00:39.157 | 07/08/201118:00:39.204 | 1310141019.000000 | 1310140599.000000 | 420.000000
...

In this case, after the 601, the results of strptime conversion start becoming inconsistent. They are missing for 1 or both the fields. Hence I cannot calculate the TotalTime from this row onwards.

601 | 07/08/201118:33:36.867 | 07/08/201118:33:36.883 | | |

602 | 07/08/201118:33:33.883 | 07/08/201118:33:33.898 | | |

603 | 07/08/201118:33:20.273 | 07/08/201118:33:20.289 | | |

604 | 07/08/201118:33:20.232 | 07/08/201118:33:20.263 | 1310140880.000000 | |

605 | 07/08/201118:33:14.398 | 07/08/201118:33:14.414 | | 1310134754.000000 |

606 | 07/08/201118:32:54.154 | 07/08/201118:32:54.169 | 1310143134.000000 | |

607 | 07/08/201118:32:39.382 | 07/08/201118:32:39.397 | | |

608 | 07/08/201118:32:27.178 | 07/08/201118:32:27.225 | | 1310141247.000000 |

609 | 07/08/201118:32:23.991 | 07/08/201118:32:24.006 | | 1310149584.000000 |

610 | 07/08/201118:32:23.950 | 07/08/201118:32:23.966 | 1310114543.000000 | |

611 | 07/08/201118:32:22.288 | 07/08/201118:32:22.303 | | 1310138962.000000 |

612 | 07/08/201118:32:17.372 | 07/08/201118:32:17.388 | | |

613 | 07/08/201118:32:12.278 | 07/08/201118:32:12.294 | | |

614 | 07/08/201118:32:05.647 | 07/08/201118:32:05.662 | 1310125505.000000 | |
...

Tags (2)
0 Karma
1 Solution

sdevadas
Path Finder

My strptime formatting was incorrect.

I used:
strptime(firsttimestr, "%m/%d/%Y%H:%M:%S.%z")

From doc I saw %z should be %q
i.e.
strptime(firsttimestr, "%m/%d/%Y%H:%M:%S.%q")

Things work well when I made the changes.

View solution in original post

0 Karma

sdevadas
Path Finder

My strptime formatting was incorrect.

I used:
strptime(firsttimestr, "%m/%d/%Y%H:%M:%S.%z")

From doc I saw %z should be %q
i.e.
strptime(firsttimestr, "%m/%d/%Y%H:%M:%S.%q")

Things work well when I made the changes.

0 Karma
Get Updates on the Splunk Community!

Fastest way to demo Observability

I’ve been having a lot of fun learning about Kubernetes and Observability. I set myself an interesting ...

September Community Champions: A Shoutout to Our Contributors!

As we close the books on another fantastic month, we want to take a moment to celebrate the people who are the ...

Splunk Decoded: Service Maps vs Service Analyzer Tree View vs Flow Maps

It’s Monday morning, and your phone is buzzing with alert escalations – your customer-facing portal is running ...