Emc IP Holding Company LLC

Amazon Technologies, Inc.

Emc IP Holding Corporation LLC

Krishna Chaitanya Gudipati

Anil Ravindranath

Rahul Ugale

Charles J Hickey

Gokul Soundararajan

Ippokratis Pandis

Naresh Chainani

Fabian Oliver Nagel

Sanjay Wangoo

Aditya Subrahmanyan

Mengchu Cai

Vijayan Prabhakaran

Sanuj Basu

Induja Sreekanthan

Chunbin Lin

Siyi Zhang

Yehan Zhang

Rajesh Parangi Sharabhalingappa

Vaishali Ravindra Narkhede

Qichen Zhang

Nikolaos Armenatzoglou

Ankil Shah

Yao Xiao

Dynamic selection of topologies for database data may be performed for performing queries. Different possible query plans for different assignments of topologies are determined for a query. One of the query plans is selected according to a cost-based model that assigns costs to different uses of the different topologies. The query is then performed using the selected query plan.

Dynamic selection of database data topologies for performing queries

Online restore may be performed between databases with different topologies while applying a custom data distribution. A request to restore a database into a different topology of nodes may be received. A plan to move different portions of the database from a current topology to the new topology made using a general distribution scheme. The plan may be performed to move the different portions of the database into the new topology and the database made available for access using the new topology. A background process may be applied to modify the distribution of the database at the new topology to match a custom distribution scheme that was implemented at the current topology.

Online restore to different topologies with custom data distribution

Techniques for resizing a distributed database are described. A request to resize a distributed database is received. The distributed database stores data organized into one or more rows of one or more tables. Each node of the first plurality of nodes is assigned a portion of the data. A portion of the data assigned to a first node in the first plurality of nodes is selected to be assigned to a second node in a second plurality of nodes. The number of nodes in the first and second plurality of nodes is different, and the first and second plurality of nodes include at least one common node. Metadata of the selected portion of the data is transferred from the first node to the second node. The metadata that includes a location of the selected portion of the data within a provider network.

In place resize of a distributed database

In one embodiment, a storage system includes a processor, a memory coupled to the processor to store instructions for execution, and an IO tagging module executed by the processor to determine a plurality of child IO requests required to complete a plurality of received IO request transactions and to tag the IO request transaction and/or the associated child IO requests with a tag identifier uniquely identifying the IO request transaction. The system includes an IO scheduler module executed by the processor to prioritize the IO request transactions according to a policy by grouping the child IO requests based on the associated tag identifier. The grouped child IO requests of the IO request transactions are serviced by a plurality of storage devices of the storage system for an optimal performance.

Transactional IO scheduler for storage systems with multiple storage devices

Described is a system (and technique) to determine an appropriate path to a storage device and scheduling a data transfer by taking into consideration bandwidth, device performance, and the nature of the transfer. The system may use an efficient implementation to reduce overhead when making such a determination by utilizing a reservation table and selecting a dispatch that is efficient for a particular data transfer. For example, the system may determine a first-fit and a future-fit scheduling for an I/O request for each path to a storage device. The system may determine completion times for each of the types of scheduling for each of the paths, and accordingly, select the path and schedule with the earliest completion time.

Topology aware load optimized multipath I/O scheduler

In one embodiment, a storage system receives a number of input/output (IO) request transactions at the storage system having multiple storage devices. For each of the IO request transactions, the system determines a number of child IO requests required to complete the IO request transaction and tags the IO request transaction and/or the associated child IO requests with a tag identifier uniquely identifying the IO request transaction within the same session. The system prioritizes the IO request transactions based on a service priority level associated with each of the IO request transaction. The system dispatches the prioritized child IO requests of the IO request transaction to storage devices, including grouping the associated child IO request to be dispatched together.

Policy driven IO scheduler to improve read IO performance in hybrid storage systems

In one embodiment, a storage system receives a number of input/output (IO) request transactions at the storage system having multiple storage devices, the IO request transactions including at least a read and a write. For each of the IO request transactions, the system determines a number of child IO requests required to complete the IO request transaction, where the child IO requests includes a write child IO request and a read child IO request. The system tags the associated child IO requests with a tag identifier uniquely identifying the IO request transaction within the same session. The system prioritizes the IO request transactions based on a service priority level and completeness of each of the IO request transactions dynamically determined at a point in time and services the child IO requests according to a prioritized order to reduce a time to complete the IO request transaction.

Policy driven IO scheduler to improve write IO performance in hybrid storage systems

In one embodiment, a storage system receives a number of input/output (IO) request transactions at the storage system having multiple storage devices. For each of the plurality of IO request transactions, the system determines a number of child IO requests required to complete the IO request transaction. The system tags the IO request transaction and/or the associated child IO requests with a tag identifier. For each of the child requests that is a write IO request, the system determines an optimal write IO request size, segments the write IO request into a number of sub-IO write requests, each having an optimal request size, and interleaves sub-IO write requests with read IO requests for servicing to avoid impact in performance to read IO requests for a mixed IO workload.

Optimized read IO for mix read/write scenario by chunking write IOs

One embodiment is related to a method for implementing a staggered solid-state drive (SSD) replacement schedule, comprising: determining whether more than a first threshold number of SSDs within an array are expected to reach End of Life (EOL) at approximately a same time; determining that the staggered SSD replacement schedule is to be engaged in response to determining that more than the first threshold number of SSDs within the array are expected to reach EOL at approximately the same time; determining the staggered SSD replacement schedule for the SSDs that are expected to reach EOL at approximately the same time; and raising replacement alerts according to the determined staggered SSD replacement schedule to prompt a user to replace the SSDs.

Method and apparatus for SSD/flash device replacement policy

In one embodiment, a storage system receives a number of input/output (IO) request transactions at the storage system having multiple storage devices. The system detects storage events associated with the storage devices, the storage events include storage device error events, storage device path error events, and solid state storage device high write amplification events. For each of the IO request transactions, the system tags a number of associated child IO requests with a tag identifier and predicts a completion time for the IO request transaction based on a completeness of the IO request transaction and detected events associated with the storage devices. The system sends the child IO requests to the storage devices to be serviced in a first order based on the predicted completion time and an arrival time of the IO request transaction so that the IO request transactions are resilient to storage events.

Policy driven IO scheduler resilient to storage subsystem performance

One embodiment is related to a method for determining a faulty hardware component within a data storage system, comprising: collecting data relating to a plurality of input/output (IO) errors associated with a first storage processor within the data storage system; compiling IO error statistics based on the data relating to the plurality of IO errors; and determining a faulty hardware component based on the IO error statistics, wherein the determining of the faulty hardware component comprises utilizing a second storage processor of the data storage system independent from the first storage processor.

Method and apparatus of a profiling algorithm to quickly detect faulty disks/HBA to avoid application disruptions and higher latencies

Embodiments are directed to a method of optimizing disk striping input/output (I/O) operations to an array of storage devices, by identifying an I/O request as a full stripe write request that stripes data across a plurality of storage devices of the array, converting the full stripe write request to a SCSI command block (CDB), and putting the SCSI command block in one of a stripe cache or a non-stripe cache that comprises a sorted linked list where each node of the linked list is a link to one of the plurality of storage devices.

Topology aware I/O scheduling for RAID storage systems

Embodiments are directed to a method of optimizing input/output (I/O) operations to a storage device having mixed read and write operations by determining a current queue state for the read and write operations with respect to defined optimum values of I/O operations per second (IOPS) and latency for the I/O operations, determining device characteristics of the storage device by determining read/write response times, queue depths and dispatch time intervals for an initial read/write operation, and modifying at least one of a wait time or batch size for subsequent read/write operations to meet the defined optimum values of IOPS and latency.

Adaptive and dynamic mixed read/write input/output balancer

A system for handling errors during interfacing with storage devices comprises a communications interface and an error handler. The error handler is for: indicating to provide a first instruction to the first storage device using the first path; determining whether an error or time out message is received; in the event the error handler determines that either message is received: indicating to provide a second instruction to the first storage device using a second path; determining whether a second error or second time out message is received; in the event the error handler determines that either message is received, indicating to provide a likely first storage device error message; and in the event the error handler determines that either message is not received, indicating to provide a likely first path error message and indicating to communicate using the second path.

Growing community of inventors

Fremont, CA, United States of America

Krishna Chaitanya Gudipati