Salesforce, Inc.

Salesforce Com, Inc.

Anup Ghatage

Venkateswararao Jujjuri

Ankit K Jain

Jayant Kumar

Colm McHugh

Sushanth Rai

Ankit Jain

Techniques are disclosed relating to storing location information about storage nodes in cookies. A cloud-based service may send location requests to an orchestration service that instantiated storage nodes included in a storage cluster of the cloud-based service. The cloud-based service may receive location information that identifies in which computer zone that a given storage node is located. The cloud-based service may store the location information in cookies at a metadata store that is shared among the storage nodes. The cloud-based service may receive, from a client node, a search request to identify ones of the storage nodes that store particular data. The cloud-based service may return a set of cookies corresponding to identified storage nodes. The set of cookies may enable the client node to determine whether there is a storage node that stores the particular data and is within the same computer zone as the client node.

Cookie-based network location of storage nodes in cloud

Techniques are disclosed for managing metadata of a distributed database system in a hybrid manner. A computer system may receive, from a computing device, a request to access a set of data stored in nodes of a distributed storage system that is a caching layer of the system. The system retrieves metadata for a set of data specified in the request, including accessing a reversemap storing a reverse-ordered copy of original metadata stored in a metadata store of the system, where the reversemap is stored on durable storage of the system. Based on retrieving the metadata from the reversemap, the system accesses nodes of the distributed storage system, where the reversemap specifies the nodes of the distributed storage system that store the set of data. The system transmits, to the computing device, information indicating a result of accessing data stored in nodes of the distributed storage system.

Hybrid database system for strongly consistent and highly scalable metadata storage

Techniques are disclosed relating to managing database queries. In some embodiments, a server system receives a query from a computer system and determines a set of aspects for the query, including at least a number of columns specified in the query and a computational cost of executing the query. The system generates a query vector based on the set of aspects determined for the query. The system then compares the query vector with a plurality of clusters, ones of the plurality of clusters comprising two or more previously generates query vectors generated based on aspects of queries previously received by the server system. Based on the comparing, specifically a distance between the query vector and the plurality of clusters of previously generated query vectors, the system classifies the query. Based on a classification of the query determined during the classifying, the system manages the query.

Anomalous query identification using query clustering

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Fremont, CA, United States of America

Anup Ghatage