9/10/2023 0 Comments Splunk transaction startswith![]() On the other hand, except for the duration between first and last events and the count of events, the transaction command does not compute statistics over the grouped events. The stats command is meant to calculate statistics on events grouped by one or more fields and discard the events (unless you are using eventstats or streamstats). Anytime you can filter the search before the first pipe, the faster the search runs.įor more examples, see the transaction command.īoth the stats command and the transaction command are similar in that they enable you to aggregate individual events together based on field values. ![]() There is no filtering before the transaction command. Additionally, this search is run over all events. You won't see it in this data, but some transactions may take a long time because the user is updating and removing items from his shopping cart before he completes the purchase. You might be curious about why the transactions took a long time, so viewing these events might help you to troubleshoot. The values in the duration field show the difference, in seconds, between the timestamps for the first and last events in the transaction. The where filter cannot be applied before the transaction command because the duration field is added by the transaction command. This example then pipes the transactions into the where command and the duration field to filter out all of the transactions that took less than a second to complete. The endswith="purchase" argument does the same for the last event in the transaction. The search defines the first event in the transaction as events that include the string, "view", using the startswith="view" argument. Sourcetype=access_* | transaction JSESSIONID clientip startswith="view" endswith="purchase" | where duration>0 This example defines a transaction as a group of events that have the same session ID, JSESSIONID, and come from the same IP address, clientip, and where the first event contains the string, "view", and the last event contains the string, "purchase". This example searches for transactions with the same session ID and IP address. Use the time range All time when you run the search. To try this example on your own Splunk instance, you must download the sample data and follow the instructions to get the tutorial data into Splunk. Transaction search example This example uses the sample data from the Search Tutorial but should work with any format of Apache web access log. To learn more, see Identify and group events into transactions in this manual. For example, an out of memory problem could trigger several database events to be logged, and they can all be grouped together into a transaction. One common use of a transaction search is to group multiple events into a single meta-event that represents a single physical event. Use the transaction command to define a transaction or override transaction options specified in nf. Any number of data sources can generate transactions over multiple log entries.Ī transaction search is useful for a single observation of any physical event stretching over multiple logged events. A transaction type is a configured transaction, saved as a field and used in conjunction with the transaction command. Although, when setting it to beyond 1000, there wasn't any boost in speed.A transaction is any group of conceptually-related events that spans time, such as a series of events related to the online reservation of a hotel room by a single customer, or a set of events related to a firewall intrusion incident. Otherwise, it would average about 80/sec. The secret sauce is the max_workers=10000. This is a modified version of what this site showed in an example. With (max_workers=10000) as executor:įutures.append(executor.submit(send, pageUrl=url))įor future in _completed(futures): Responses = #output content of each request as string in an array import timeįor y in range(5000):urls.append(""+str(y)) You may have to pip install for concurrent and requests. This works, getting around 250+ requests a second. The input should be an array or URLs and the output an array of the html string. I'm trying to avoid AIOHTTP as the rigmarole of setting it up was a pain, which didn't even work. I've searched everywhere, but get no Python 3.11+ answer or one that doesn't give me errors. I know this would have to be concurrent requests due to my goal being 150 to 500+ requests a second. I'm trying to send HTTPS requests as quickly as possible.
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