Splunk Inc.

Christopher Madden Pride

Sourav Pal

Arindam Bhattacharjee

Ashish Mathew

Xiaowei Wang

Alexandros Batsakis

Alexander Douglas James

James Monschke

Bharath Kishore Reddy Aleti

James Alasdair Robert Hodge

Mustafa Ahamed

Arun Ramani

Manu Jose

Scott Calvert

Vishal Patel

David Marquardt

Nicholas Robert Romito

Andrew Peters

Hailun Yan

Ankit Jain

Bei Li

Igor Braylovskiy

Sogol Moshtaghi

Steve Yu Zhang

Ledion Bitincka

David Everett Simmen

Igor Stojanovski

Thomas Allan Haggie

Clint Sharp

Eric Sammer

Joseph Gabriel Echeverria

Sai Krishna Sajja

Karthikeyan Sabhanatarajan

Murugan Kandaswamy

Marc Andre Chene

Amrittpal Singh Bath

Pratiksha Shah

Brad Lovering

Esguerra Ma Kharisma

Clifton Gordon

Disclosed is a data fabric service system that can be implemented in a distributed computer network, such as a data intake and query system. The data index and query system can receive a search query and define a search scheme for applying the search query on distributed data storage systems including internal data storage and external data storage. The data index and query system may provide a portion of the search scheme to a search service of the data fabric service system, which can cause worker nodes of the data fabric service system to perform various functions—including applying the search query to the external data storage based on the portion of the search scheme in order to obtain search results.

Data search and analysis for distributed data systems

The disclosed embodiments include a method performed by a data intake and query system. The method includes receiving a search query by a search head, defining a search process for applying the search query to indexers, delegating a first portion of the search process to indexers and a second portion of the search process to intermediary node(s) communicatively coupled to the search head and the indexers. The first portion can define a search scope for obtaining partial search results of the indexers and the second portion can define operations for combining the partial search results by the intermediary node(s) to produce a combination of the partial search results. The search head then receives the combination of the partial search results, and outputs final search results for the search query, where the final search results are based on the combination of the partial search results.

Multi-phased execution of a search query

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives raw machine data at an indexing system, and stores at least a portion of the raw machine data in buckets using containerized indexing nodes instantiated in a containerized environment. The data intake and query system stores the buckets in a shared storage system.

Processing data using containerized nodes in a containerized scalable environment

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched and search nodes to execute the query. The data intake and query system maps the identified buckets to the search nodes and executes the query using the identified bucket and search nodes.

Managing efficient query execution including mapping of buckets to search nodes

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system uses a search node catalog to identify search nodes that are available to execute the query and uses a bucket catalog to identify buckets to be searched. The data intake and query system executes the query using the identified bucket and search nodes.

Identifying buckets for query execution using a catalog of buckets

Systems and methods are disclosed for processing and executing queries against one or more dataset. As part of processing the query, the system determines whether the query is susceptible to a significantly imbalanced partition. In the event, the query is susceptible to an imbalanced partition, the system monitors the query and determines whether to perform a multi-partitioning determination to avoid a significantly imbalanced partition.

Multi-partitioning data for combination operations

Disclosed is a data fabric service system that can be implemented in a distributed computer network, such as a data intake and query system. The data index and query system can receive a search query and define a search scheme for applying the search query on distributed data storage systems including internal data storage and external data storage. The data index and query system may provide a portion of the search scheme to a search service of the data fabric service system, which can cause worker nodes of the data fabric service system to perform various functions&#x2014;including applying the search query to the external data storage based on the portion of the search scheme in order to obtain search results.

Data fabric service system deployment

Multi-threaded processing of search responses returned by search peers is disclosed. An example method may include transmitting, by a computer system, a search request to a plurality of search peers of a data aggregation and analysis system; receiving, by a first processing thread, a plurality of data packets from the plurality of search peers; parsing, by a second processing thread, one or more data packets of the plurality of data packets to produce a first partial response to the search request; parsing, by a third processing thread, the one or more data packets to produce a second partial response to the search request; and generating, based on the first partial response and the second partial response, an aggregated response to the search request.

Multi-threaded processing of search responses

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system parses the query and uses a metadata catalog to dynamically identify configuration parameters of datasets and/or rules associated with the query. The identified configuration parameters are communicated to a query processing component of the data intake and query system for use in executing the query.

Identifying configuration parameters for a query using a metadata catalog

Systems and methods are disclosed for annotating a metadata catalog in a data intake and query system based on a query received by the data intake and query system. The metadata catalog can store information about datasets associated with the data intake and query system, including dataset configuration records of the datasets, which can be used to process queries for execution by the data intake and query system. The data intake and query system can receive a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system can parse the query to identify datasets and/or data fields associated with the query. Based on the identified datasets and/or fields, the data intake and query system can generate one or more annotations, and use the annotations to update the metadata catalog.

Revising catalog metadata based on parsing queries

Systems and methods are disclosed for mapping search nodes to a search head in a data intake and query system based on a tenant identifier in order to execute a query received by the data intake and query system. The mapping may allow same or similar search nodes to be used to execute queries that are associated with a particular tenant identifier, in order to take advantage of caching and local data stored with those search nodes. In some cases, search nodes can be mapped based on the tenant identifier using a hashing algorithm, such as a consistent hashing algorithm.

Dynamically assigning a search head to process a query

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched and stores a copy of buckets in memory associated with one or more search nodes. A search node performs a search on buckets residing in its memory.

Copying buckets from a remote shared storage system to memory associated with a search node for query execution

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched. The data intake and query system performs a hash on bucket identifiers of the identified buckets to identify search nodes to search the buckets.

Hashing bucket identifiers to identify search nodes for efficient query execution

Multi-partitioning for combination operations

Growing community of inventors

San Francisco, CA, United States of America

Christopher Madden Pride