Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes receiving, by a processing device, a plurality of images as search results returned based at least in part on a search string for an item in the form of a tuple including an item class, an action and an actor. The method further includes determining, by the processing device, whether the search string is effective at indicating a common item use based on image similarity. The method further includes, based at least in part on determining that the search string is ineffective at indicating the item use, generating, by the processing device, an alternative search string.

Abstract: In a data storage system with a number of replicas of a file set to one or more replicas, a timer is set to track a time since a last access to the file. Responsive to the timer matching a first timer window threshold, the timer is reset to count to a second timer window threshold and a number of replicas of the file are automatically reduced within the data storage system, wherein the probability that the file will be accessed prior to the first timer window threshold is greater than the probability that the file will be accessed after the first timer window threshold. Responsive to the timer matching the second timer window threshold, the timer is reset to count to a third timer window threshold. Responsive to receiving a read access prior to the timer reaching the third timer window threshold, the number of replicas of the file is increased and the timer reset to count to the second timer window threshold.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes receiving, by a processing device, a plurality of images returned as results to an executed search string in the form of a tuple including an item class, an action and an actor. The method further includes generating, by the processing device, a collection similarity score by comparing at least one of the plurality of images to at least one other of the plurality of images. The method further includes determining, by the processing device, whether the collection similarity score exceeds a collection threshold. The method further includes, based at least in part on determining that the similarity score does not exceed the collection threshold, indicating that the search string is ineffective at indicating the item use.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes receiving, by a processing device, an item identifier. The method further includes retrieving, by the processing device, an item description based at least in part on the item identifier. The method further includes identifying, by the processing device, a tuple indicating a common item use based at least in part on the item description. The method further includes constructing, by the processing device, a search string based at least in part on the tuple. The method further includes retrieving, by the processing device, at least one image based at least in part on the search string.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes constructing, by a processing device, a search string based at least in part on a tuple including an item class, an action, and an actor. The method further includes retrieving, by the processing device, a plurality of images based at least in part on the search string for an item. The method further includes evaluating, by the processing device, the retrieved plurality of images based on a similarity to determine whether the search string is effective at indicating a common item use. The method further includes, based at least in part on determining that the search string is ineffective at indicating the item use, generating, by the processing device, an alternative search string.

Abstract: In a data storage system with a number of replicas of a file set to one or more replicas, a timer is set to track a time since a last access to the file. Responsive to the timer matching a first timer window threshold, the timer is reset to count to a second timer window threshold and a number of replicas of the file are automatically reduced within the data storage system, wherein the probability that the file will be accessed prior to the first timer window threshold is greater than the probability that the file will be accessed after the first timer window threshold. Responsive to the timer matching the second timer window threshold, the timer is reset to count to a third timer window threshold. Responsive to receiving a read access prior to the timer reaching the third timer window threshold, the number of replicas of the file is increased and the timer reset to count to the second timer window threshold.

Abstract: In a data storage system with a number of replicas of a file set to one or more replicas, a timer is set to track a time since a last access to the file. Responsive to the timer matching a first timer window threshold, a number of replicas of the file are automatically reduced within the data storage system, wherein the probability that the file will be accessed prior to the first timer window threshold is greater than the probability that the file will be accessed after the first timer window threshold.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes receiving, by a processing device, an item identifier. The method further includes retrieving, by the processing device, an item description based at least in part on the item identifier. The method further includes identifying, by the processing device, a tuple indicating a common item use based at least in part on the item description. The method further includes constructing, by the processing device, a search string based at least in part on the tuple. The method further includes retrieving, by the processing device, at least one image based at least in part on the search string.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes receiving, by a processing device, a plurality of images as search results returned based at least in part on a search string for an item in the form of a tuple including an item class, an action and an actor. The method further includes determining, by the processing device, whether the search string is effective at indicating a common item use based on image similarity. The method further includes, based at least in part on determining that the search string is ineffective at indicating the item use, generating, by the processing device, an alternative search string.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes receiving, by a processing device, a plurality of images returned as results to an executed search string in the form of a tuple including an item class, an action and an actor. The method further includes generating, by the processing device, a collection similarity score by comparing at least one of the plurality of images to at least one other of the plurality of images. The method further includes determining, by the processing device, whether the collection similarity score exceeds a collection threshold. The method further includes, based at least in part on determining that the similarity score does not exceed the collection threshold, indicating that the search string is ineffective at indicating the item use.

Abstract: Examples of techniques for constructing, evaluating, and improving a search string for retrieving images are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes constructing, by a processing device, a search string based at least in part on a tuple including an item class, an action, and an actor. The method further includes retrieving, by the processing device, a plurality of images based at least in part on the search string for an item. The method further includes evaluating, by the processing device, the retrieved plurality of images based on a similarity to determine whether the search string is effective at indicating a common item use. The method further includes, based at least in part on determining that the search string is ineffective at indicating the item use, generating, by the processing device, an alternative search string.

Abstract: Systems, methods, and computer-readable media for automatically seeding an API into a natural language conversational interface are described herein. An API is automatically seeded into a natural language conversational interface by mapping a set of API calls to a set of intents, mapping the set of intents to a collection of example utterances, and using the collection of example utterances as input training data to train a natural language classifier. The trained classifier may then be used to determine an intent associated with a received query such that an action associated with the determined intent can then be performed.

Abstract: In a data storage system with a number of replicas of a file set to one or more replicas, a timer is set to track a time since a last access to the file. Responsive to the timer matching a first timer window threshold, a number of replicas of the file are automatically reduced within the data storage system, wherein the probability that the file will be accessed prior to the first timer window threshold is greater than the probability that the file will be accessed after the first timer window threshold.

Abstract: In a distributed file system with a number of replicas of a file set to two or more replicas, a computer sets a timer to track a time since a last access to the file, wherein the replicas of the file are distributed across two or more nodes within the distributed file system. Responsive to an access to the file prior to the timer reaching a first timer window threshold, the computer resets the timer. Responsive to the timer matching a first timer window threshold, the computer automatically reduces a number of replicas of the file within the distributed file system, wherein the probability that the file will be accessed prior to the first timer window threshold is greater than the probability that the file will be accessed after the first timer window threshold.

Abstract: Embodiments include a method, system, and computer program product for managing workloads in a network. A switch receives data associated with a workload. The received data is tagged with an identifier that associates the data with the workload. The received data is compressed based on determining that second data stored in a buffer of the switch exceeds a threshold. The switch stores the compressed data in the buffer. The compressed data is transmitted to a second network based on a determination that the switch is over-subscribed.

Abstract: Embodiments include a method, system, and computer program product for managing workloads in a network. A switch receives data associated with a workload. The received data is tagged with an identifier that associates the data with the workload. The received data is compressed based on determining that second data stored in a buffer of the switch exceeds a threshold. The switch stores the compressed data in the buffer. The compressed data is transmitted to a second network based on a determination that the switch is over-subscribed.

Abstract: Embodiments include a method, system, and computer program product for allocating data to storage in a network. A data item accessed by a server in the network is identified. A controller classifies the identified data item based on at least one of: a frequency of access requests for the data item by the server and an access time associated with providing the data item to the server once the server requests the data item. A memory of a switch in the network is selected for storing the data item based on the classification of the data item. The controller causes the data item to be stored in the memory of the switch, from which the data item is accessed by the server upon request.

Abstract: Embodiments include a method, system, and computer program product for allocating data to storage in a network. A data item accessed by a server in the network is identified. A controller classifies the identified data item based on at least one of: a frequency of access requests for the data item by the server and an access time associated with providing the data item to the server once the server requests the data item. A memory of a switch in the network is selected for storing the data item based on the classification of the data item. The controller causes the data item to be stored in the memory of the switch, from which the data item is accessed by the server upon request.

Abstract: In a distributed file system with a number of replicas of a file set to two or more replicas, a computer sets a timer to track a time since a last access to the file, wherein the replicas of the file are distributed across two or more nodes within the distributed file system. Responsive to an access to the file prior to the timer reaching a first timer window threshold, the computer resets the timer. Responsive to the timer matching a first timer window threshold, the computer automatically reduces a number of replicas of the file within the distributed file system, wherein the probability that the file will be accessed prior to the first timer window threshold is greater than the probability that the file will be accessed after the first timer window threshold.

Abstract: A data management system receives a query. A query optimizer determines an access plan for the query. The access plan has a plurality of stages, where each stage may have a different degree of parallelism for processing threads executing the stage. The query optimizer determines a maximum degree of parallelism for the plurality of stages and reserves processor cores based on the maximum degree of parallelism. The data management system schedules threads on the reserved processor cores for a first stage of the access plan. The data management system changes simultaneous multi-threading (SMT) mode for the processor cores when a second stage of the access plan having a different degree of parallelism is executed.