Hewlett Packard Enterprise Development LP

Nimble Storage, Inc.

Splunk Inc.

Vanco Buca

Umesh Maheshwari

Gurunatha Karaje

Tomasz Barszczak

Ajay Gulati

Senthil Kumar Ramamoorthy

Pradeep Shetty

Sandeep Karmarkar

Xiaowei Wang

Asha Andrade

Mandar Samant

Sourabh Yerfule

Zhaosheng Zhu

Tingting Bao

Weichao Duan

Anuradha Pariti

The disclosed implementations include a method performed by a data intake and query system. The method includes receiving a search query at a search head, the search query including a branching operation between sets of data, generating a first subquery and a second subquery corresponding to the sets of data for execution by a search node, generating instructions for an intermediary node to combine partial results of the first subquery and the second subquery and instructions to concurrently communicate the subqueries to a search node, and executing the query by providing the instructions for the intermediary node to the intermediary node and the subqueries to the search node, the intermediary node receiving sets of partial search results for the subqueries, performing at least a portion of the branching operation on the partial results, and communicating the combined results to another intermediary node or the search head.

Parallel branch operation using intermediary nodes

Methods, systems, and programs are presented for controlling the flow of data into a device in the presence of writes that are unaligned along boundaries associated with a block size. One method includes operations for identifying admission data rates for volumes, and for tracking a utilization rate of a memory that stores data of incoming writes. The method determines if incoming writes include unaligned data. When the memory utilization rate is above a first threshold, a first flow control is applied that includes a reduction of admission rates of volumes having unaligned writes while maintaining admission rates of volumes without unaligned writes. When the utilization rate is above a second threshold that is greater than the first threshold, a second flow control is applied in addition to the first flow control. The second flow control includes a reduction of a system admission rate for all incoming writes.

Flow control for unaligned writes in network storage device

Methods, systems, and computer programs are presented for allocating CPU cycles in a storage system. One method includes operations for receiving requests to be processed, and for associating each request to one task. A foreground task is for processing input/output requests, and the foreground task includes one or more flows. Each flow is associated with a queue and a flow counter value, where each queue is configured to hold requests. The method further includes an operation for selecting one task for processing by the CPU based on an examination of the number of cycles processed by the CPU for each task. When the selected task is the foreground task, the flow having the lowest flow counter is selected. The CPU processes a request from the queue of the selected flow, and the flow counter of the selected flow is increased based on the data consumption of the processed task.

Quality of service implementation in a networked storage system with hierarchical schedulers

Methods, systems, and computer programs are presented for allocating CPU cycles and disk Input/Output's (IOs) to resource-creating processes based on dynamic weights that change according to the current percentage of resource utilization in the storage device. One method includes operations for assigning a first weight to a processing task that increases resource utilization of a resource for processing incoming input/output (IO) requests, and for assigning a second weight to a generating task that decreases the resource utilization of the resource. Further, the method includes an operation for dynamically adjusting the second weight based on the current resource utilization in the storage system. Additionally, the method includes an operation for allocating the CPU cycles and disk IOs to the processing task and to the generating task based on their respective first weight and second weight.

Network storage device using dynamic weights based on resource utilization

Methods and systems are presented for allocating CPU cycles among processes in a storage system. One method includes operations for maintaining segments in a first memory, each segment including blocks, and for maintaining a block temperature for each block in a second memory. The first memory is a read-cache where one segment is written at a time, and each block is readable from the first memory without reading the corresponding complete segment. The block temperature is based on the frequency of access to the respective block, and a segment temperature is based on the block temperature of its blocks. Additionally, the segment with the lowest segment temperature is selected for eviction from the second memory, and blocks in the selected segment with a block temperature greater than a threshold temperature are identified. The selected segment is evicted, and a segment with the identified blocks is written to the first memory.

Access-based eviction of blocks from solid state drive cache memory

Methods and systems are presented for evicting or copying-forward blocks in a storage system during garbage collection. In one method, a block status is maintained in a first memory to identify if the block is active or inactive, blocks being stored in segments that are configured to be cacheable in a second memory, a read-cache memory. Whenever an operation on a block is detected making the block inactive in one volume, the system determines if the block is still active in any volume, the block being cached in a first segment in the second memory. When the system detects that the first segment is being evicted from the second memory, the system re-caches the block into a second segment in the second memory if the block status of the block is active and the frequency of access to the block is above a predetermined value.

Cache eviction of inactive blocks using heat signature

Congestion avoidance in network storage device using dynamic weights

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San Jose, CA, United States of America

Vanco Buca