I've found many times the image-package-extractor is unable to extract packages from some images I'm running because the daemon set creates the pods with 50MB of memory request, and the same ammount for it's limits.
kubectl edit ds image-package-extractor --namespace=kube-system
error: daemonsets.apps "image-package-extractor" could not be patched: daemonsets.apps "image-package-extractor" is forbidden: User "jk" cannot patch resource "daemonsets" in API group "apps" in the namespace "kube-system": GKE Warden authz [denied by managed-namespaces-limitation]: the namespace "kube-system" is managed and the request's verb "patch" is denied
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kubectl replace -f /tmp/kubectl-edit-751860510.yaml
Error from server (Forbidden): error when replacing "/tmp/kubectl-edit-751860510.yaml": daemonsets.apps "image-package-extractor" is forbidden: User "jk" cannot update resource "daemonsets" in API group "apps" in the namespace "kube-system": GKE Warden authz [denied by managed-namespaces-limitation]: the namespace "kube-system" is managed and the request's verb "update" is denied
I created a field extractor for different fields for an event. Now I would like to search all the events from a source and apply that field extractor to see the fields that I'm interested in. The field extractor seems to appear, but I don't know how to apply that into my search. I've tried REPORT- but no luck. How can I apply a field extractor already created into a search ?
Now, in 2024, 7 years later it is still not very clear how one applies a saved extraction regex to an existing search to extract fields from the search. Especially without access to the various server side configuration files. Splunk has grown long in the tooth, dementia encroaching.
Reality: You probably can't do it simply.
If you have a sourcetype X. The extractors you saved will only run against the base, plain data set sent as X, not against your search, and they run against the base sourcetype automatically. If it was going to work, it would already be working and you would already have your field.
Now, if your search does any kind of transformations like for example pulling log fields out of JSON data using spath, messing around with _raw or similar, the extractor you created isn't going to run against that resulting data set. I know, I've tried. The extractors get applied before that part of the search runs.
You're going to have to go into Settings -> Fields -> Field Extractions and copy/paste the regex created by the web extractor page into your search and manually extract the field within your search using the "rex" command. You may have to tweak it slightly especially for quotes.
It's a little disingenuous of the splunk web extraction generator to take the results of the current search as the input and imply that a saved extractor will actually operate against such a search and pull fields out for you. It doesn't.
Not a useful answer. The question concerned a field extractor, not a transform. Are you implying that the ONLY way Splunk can use a field-extractor is to first create a transform? Pity, since that seems beyond the scope of an ordinary user.
I have the same issue here. And I cannot access the transforms.conf file (or the server's file system at all) to get the Stanza of my field extractor.
In the Splunk Web-UI in the field extractions overview, the name of my field extractor is like my_sourcetype : EXTRACT-my_new_field.
Is there any other way to derive the Stanza through the Splunk Web-UI?
An extractor object is an object with an unapply method. Whereas the apply method is like a constructor which takes arguments and creates an object, the unapply takes an object and tries to give back the arguments. This is most often used in pattern matching and partial functions.
Thanks for your response @AndyMenon . There are few risk factors which we could find in our process. Main thing is it is not a readable pdf to go with regex extractors. It is the scanned pdf where digitizing the document mostly getting in to an error with regex as the digitized scanned docs getting more special characters. We have ruled out the regex extractors in this documents.
I am using TrOCRProcessor and giving the same message
Could not find image processor class in the image processor config or the model config. Loading based on pattern matching with the model's feature extractor configuration.
The inference of the image processor from the feature extractor name is done, as this allows for a smooth deprecation cycle of the feature extractors, where older configs can be used without breaking changes.
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The L|Flux 800i Fume Extractor functions are fully automatic. All the user has to do is set the appropriate airflow on installation. A dedicated control, monitoring, and display system unique to this fume extractor. The L|Flux filter monitor units are in all digital units; which is highly recommended for gases and chemicals emitted.
1.5 Gallon Portable Carpet Spotter and shampooer with Floor Wand, Detail Tool, and 9' Water and Vacuum Hose. The Aqua Pro Vac is a portable, quiet, lightweight, and extremely powerful machine. It has a 1100w vacuum motor and a water pump that works at 58 psi with a flow rate of 1/2 gallon per minute. It is perfect for touch-up cleaning, spot removal between scheduled carpet cleanings, and congested areas and stairs where larger extractors just won't fit. The Aqua Pro Vac takes the hassle out of cleaning spots before they become major stains. It is available in three configurations for spot cleaning in hospitals and hotels, small area carpet cleaning in residential homes, apartment buildings, and automotive detailing.
This is a commercial grade cold water extractor perfect for auto detailing or cleaning houses or furniture. The machine includes both an upholstery head perfect for upholstered car seats and carpets and also a wider floor head that is mounted on a stainless steel vacuum pole enabling you to use the machine on larger areas such as rooms. The canister design allows easier mobility and is mounted on easy motion casters and two lateral fixed wheels and with a 9 foot long hose getting an and around the average vehicle is effortless. The powerful 1100 vacuum motor is isolated with it's own switch, and the water pump has it's own dedicated switch too, this allows the operator to stop the water flow when necessary or visa versa stop the vacuum and just spray...making it versatile. Different from a shampooer, this extractor has two separate removable compartments or water reservoirs, one for clean solution and one for dirty water. These compartments are removable, so they're easy to empty or fill with warm or cold water. The machine is light enough to be hand carried (although we don't recommend carrying it full of water!) and it's small enough to fit into a compact car or a small truck. Perfect for the mobile auto detailing community.
First, you need to vacuum the carpet or upholstery to remove any particles like dust or debris.
Over the past 10 years the best practices that has emerged from mobile auto detailers involves using a detergent mixed with water in a spray bottle spraying this mixture on the carpet and using a drill bit brush to agitate the pile. Then use the clean water from the extractor to remove the dirt.... you wont' believe your eyes when you see the dirt being sucked away.
Some extractors provide a way to configure the extraction process. To configure an extractor, pass its configuration object to the resource's .app_data() method. In the case of Json extractor it returns a JsonConfig. You can configure the maximum size of the JSON payload as well as a custom error handler function.
In RelativityOne, you can use the log extractor to access logs for a custom application. You can view logs for a date range of seven days or less, which your custom application has generated in the last 21 days. The log extractor accesses the logs and displays them as JSON output on a new tab in your browser where you can view or download them.
UserWarning: Parsing of message: 'i wanna get a blue car' lead to overlapping entities: blue of type colour extracted by RegexEntityExtractor overlaps with blue of type colour extracted by DIETClassifier. This can lead to unintended filling of slots. Please refer to the documentation section on entity extractors and entities getting extracted multiple times: -extractors
For granular or coarse products, such as metallic gels, algae and marine products that sink in solvent or products that are too fine or coarse for percolation-type extractors, the Model IV Immersion Extractor processes virtually any product with a density greater than the solvent. Typical products include algae, hemp / hemp seeds, botanicals, fermentation products, metallic gels and contaminated soils.
In the past, the extraction of fine, powdery material was usually carried out in a batch process due to the limitation of screen filtration in continuous extractor designs. Basically, fine materials would flow through the screen.
The CodeQL CLI uses special programs, called extractors, to extract information from the source code of a software system into a database that can be queried. You can customize the behavior of extractors by setting extractor configuration options through the CodeQL CLI.
Each extractor defines its own set of configuration options. To find out which options are available for a particular extractor, you can run codeql resolve languages or codeql resolve extractor with the --format=betterjson option. The betterjson output format provides the root paths of extractors and additional information. The output of codeql resolve extractor --format=betterjson will often be formatted like the following example: 0852c4b9a8
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