Oracle International Corporation

Kothanda Umamageswaran

Jia Shi

Juan R Loaiza

Alexander Tsukerman

Zuoyu Tao

Selcuk Aya

Krishnan Meiyyappan

Vijay Sridharan

Boris Erlikhman

Alex Tsukerman

Nilesh Choudhury

Adrian Tsz Him Ng

Wei Zhang

Wei-Ming Hu

Neil J S MacNaughton

Kiran Badrinarain Goyal

Semen Ustimenko

Tirthankar Lahiri

Adam Y Lee

Umesh Panchaksharaiah

Bharat C V Baddepudi

Sumanta Kumar Chatterjee

J William Lee

Roger J Hansen

Adrian Ng

Vivekanandhan Raja

Richard L Frank

Dmitry Mikhailovich Potapov

Vasudha Krishnaswamy

Sanket Hase

Kartik Kulkarni

Vipin Gokhale

Eugene Reddy Ho

David Friedman

Poojan Kumar

Sue-Kyoung Lee

Vijayakrishnan Nagarajan

Bang Nguyen

Zheren R Zhang

Timothy L Shetler

Justin Matthew Lewis

Susy Fan

Scott Martin

Amit Ganesh

Shasank Kisan Chavan

Yunrui Li

Jesse Kamp

Roger MacNicol

Bharat Chandra Baddepudi

Graham Ivey

Viral Shah

Xia Hua

Akshay Shah

Sarat B Kakarla

Allen Brumm

Kesavan P Srinivasan

Roger Dermot Macnicol

James Stenoish

Maria Colgan

Daniel McClary

Robert K Abbott

Kishy Kumar

Shih-Yu Huang

Laura Liaoruo Wang

Devang Mundhra

Kai Zhang

Yinian Qi

Salini Selvaraj Kowsalya

Nilesh Coudhury

Huy Nguyen

Somayeh Sardashti

Johnny Quan Zhou

Tsz Him (Adrian) Ng

Masakazu Bando

Yiliang Jin

Yiran Qin

Ke Hu

Xin Zeng

Zuoyo Tao

Mingmin Chen

Roger D Macnicol

Neil JS Macnaughton

Zheren Zhang

Juan R Loiza

Kiran B Goyal

Aya Selcuk

Bharat CV Baddepudi

Roger Hansen

Region summaries of database data are stored in persistent memory of a storage cell. Because the region summaries are stored in persistent memory, when a storage cell is powered off and data in volatile memory is not retained, region summaries are nevertheless preserved in persistent memory. When the storage cell comes online, the region summaries already exist and may be used without the delay attendant to regenerating the region summaries stored in volatile memory.

Storing derived summaries on persistent memory of a storage device

Techniques are described for providing one or more clients with direct access to cached data blocks within a persistent memory cache on a storage server. In an embodiment, a storage server maintains a persistent memory cache comprising a plurality of cache lines, each of which represent an allocation unit of block-based storage. The storage server maintains an RDMA table that include a plurality of table entries, each of which maps a respective client to one or more cache lines and a remote access key. An RDMA access request to access a particular cache line is received from a storage server client. The storage server identifies access credentials for the client and determines whether the client has permission to perform the RDMA access on the particular cache line. Upon determining that the client has permissions, the cache line is accessed from the persistent memory cache and sent to the storage server client.

PMEM cache RDMA security

Described is an improved approach to implement fast detection of node death. Instead of just relying on multiple heart beats to fail in order to determine whether a node is dead, the present approach performs an on demand validation using RDMA to determine whether the node is reachable, where the approach of using RDMA is significantly faster than the heartbeat approach.

Fast node death detection

Techniques related to a server-side extension of client-side caches are provided. A storage server computer receives, from a database server computer, an eviction notification indicating that a data block has been evicted from the database server computer's cache. The storage server computer comprises a memory hierarchy including a volatile cache and a persistent cache. Upon receiving the eviction notification, the storage server computer retrieves the data block from the persistent cache and stores it in the volatile cache. When the storage server computer receives, from the database server computer, a request for the data block, the storage server computer retrieves the data block from the volatile cache. Furthermore, the storage server computer sends the data block to the database server computer, thereby causing the data block to be stored in the database server computer's cache. Still further, the storage server computer evicts the data block from the volatile cache.

Server-side extension of client-side caches

A method and an apparatus for implementing a buffer cache for a persistent file system in a non-volatile memory is provided. A set of data is maintained in one or more extents in a non-volatile random-access memory (NVRAM) of a computing device. At least one buffer header is allocated in a dynamic random-access memory (DRAM) of the computing device. In response to a read request by a first process executing on the computing device to access one or more first data blocks in a first extent of the one or more extents, the first process is granted direct read access of the first extent in the NVRAM. A reference to the first extent in the NVRAM is stored in a first buffer header. The first buffer header is associated with the first process. The first process uses the first buffer header to directly access the one or more first data blocks in the NVRAM.

Directly mapped buffer cache on non-volatile memory

Techniques are provided to adjust the behavior of a cache based on a count of cache misses for items recently evicted. In an embodiment, a computer responds to evicting a particular item (PI) from a cache by storing a metadata entry for the PI into memory. In response to a cache miss for the PI, the computer detects whether or not the metadata entry for the PI resides in memory. When the metadata entry for the PI is detected in memory, the computer increments a victim hit counter (VHC) that may be used to calculate how much avoidable thrashing is the cache experiencing, which is how much thrashing would be reduced if the cache were expanded. Either immediately or arbitrarily later, the computer adjusts a policy of the cache based on the VHC's value. For example, the computer may adjust the capacity of the cache based on the VHC.

Detection of avoidable cache thrashing for OLTP and DW workloads

The techniques described herein limit client utilization of a parallel-access storage device. Specifically, client utilization of a particular storage device is estimated using I/O cost metrics to estimate the costs of I/O requests from the client to the particular storage device. The I/O cost metrics are determined based on calibration-based system performance data, which represents a system-wide measure of storage device performance for a system in which the particular storage device resides. The calibration-based system performance data includes one or both of composite throughput data and composite IOPS data for multiple parallel-access devices in the system. The cost estimates for I/O requests issued from a client to a parallel-access device are tracked in a total cost estimate for the client. Client utilization of the storage device, as tracked by the total cost estimate for the client, is limited to a percentage of the total estimated bandwidth of the storage device.

Consistently enforcing I/O resource constraints for workloads on parallel-access storage devices

Data blocks are cached in a persistent cache ('NV cache') allocated from as non-volatile RAM ('NVRAM'). The data blocks may be accessed in place in the NV cache of a &#x201c;source&#x201d; computing element by another &#x201c;remote&#x201d; computing element over a network using remote direct memory access (&#x201c;RMDA&#x201d;). In order for a remote computing element to access the data block in NV cache on a source computing element, the remote computing element needs the memory address of the data block within the NV cache. For this purpose, a hash table is stored and maintained in RAM on the source computing element. The hash table identifies the data blocks in the NV cache and specifies a location of the cached data block within the NV cache.

Non-volatile cache access using RDMA

A storage system communicatively coupled to a database management system (DBMS performs storage-side scanning of data sources that are not stored in native database storage format of the DBMS. Data sources for external tables are accessible in a storage system referred to as a distributed data access system (DDAS), e.g. a Hadoop Distributed File System. To execute a query that references an external table, a DBMS first generates an execution plan. The DDAS supplies the DBMS with information that specifies each portion of the data source, and specifies which data node to use to access the portion. The DBMS sends a request for each portion to the respective data node, requesting that the data node generate rows from data in the portion. The request may specify scanning criteria, specifying one or more columns to project and/or filter on, and code modules for the data node to execute to generate records.

Storage-side scanning on non-natively formatted data

Techniques related to failover to the secondary storage server from a primary storage server of a database server without degrading the performance of servicing storage requests for client applications are provided. In an embodiment, the secondary storage server receives, from the database server, an eviction notification indicating that a set of data blocks has been evicted from a cache. The secondary storage server's memory hierarchy includes a secondary cache and a secondary persistent storage that stores a second copy of the set of data blocks. The secondary storage server persistently stores a copy of data, which is also persistently stored on the primary storage server, which includes a first copy of the set of data blocks. In an embodiment, upon receiving the eviction notification, the secondary storage server retrieves the second copy of the set of data blocks from the secondary persistent storage of the secondary storage server and loads the second copy of the set of data blocks into the secondary cache. After an interruption event, the secondary storage receives a request for a subset of the set of data blocks based on a request for data, at the database server. Upon receiving the request for the subset of the set of data blocks, the second storage server retrieves the subset of the set of data blocks from the second copy of the set of data blocks stored on the secondary cache of the secondary storage server without retrieving any of such data blocks from the second copy of the set of data blocks stored on the persistent storage of the secondary storage server. The second storage server sends the subset of the set of data blocks to the database server.

Secondary storage server caching

A shared storage architecture persistently stores database files in non-volatile random access memories (NVRAMs) of computing nodes of a multi-node DBMS. The computing nodes of the multi-node DBMS not only collectively store database data on NVRAMs of the computing nodes, but also host database server instances that process queries in parallel, host database sessions and database processes, and together manage access to a database stored on the NVRAMs of the computing nodes. To perform a data block read operation from persistent storage, a data block may be transferred directly over a network between NVRAM of a computing node that persistently stores the data block to a database buffer in non-volatile RAM of another computing node that requests the data block. The transfer is accomplished using remote direct memory access ('RDMA).

Database with NVDIMM as persistent storage

A method and apparatus for intelligent network resource manager for distributed computing systems is provided. A first priority is assigned to a first virtual channel set that includes at least two virtual channels of a plurality of virtual channels associated with a physical communication channel. A second priority is assigned to a second virtual channel set that includes at least one virtual channel of the plurality of virtual channels. The first virtual channel set has more virtual channels than the second virtual channel set. Outbound messages of the first priority are directed to virtual channels of the first virtual channel set. Outbound messages of the second priority are directed to virtual channels of the second virtual channel set. The virtual channels are processed in a round-robin order, where processing includes sending the outbound messages over the physical communication channel.

Intelligent network resource manager

A shared storage architecture persistently stores database files in non-volatile random access memories (NVRAMs) of computing nodes of a multi-node DBMS. The computing nodes of the multi-node DBMS not only collectively store database data on NVRAMs of the computing nodes, but also host database server instances that process queries in parallel, host database sessions and database processes, and together manage access to a database stored on the NVRAMs of the computing nodes. To perform a data block read operation from persistent storage, a data block may be transferred directly over a network between NVRAM of a computing node that persistently stores the data block to a database buffer in non-volatile RAM of another computing node that requests the data block. The transfer is accomplished using remote direct memory access ('RDMA). In addition to techniques for performing a data block read operation to NVRAM, computing nodes perform a data block write operation to data blocks stored in NVRAM of the NVRAM shared storage architecture. The data block write operation is referred to herein as a one-sided write because only one database process needs to participate in the writing of a data block to NVRAM in order to successfully commit the write.

Remote one-sided persistent writes

A method and apparatus for implementing a buffer cache for a persistent file system in non-volatile memory is provided. A set of data is maintained in one or more extents in non-volatile random-access memory (NVRAM) of a computing device. At least one buffer header is allocated in dynamic random-access memory (DRAM) of the computing device. In response to a read request by a first process executing on the computing device to access one or more first data blocks in a first extent of the one or more extents, the first process is granted direct read access of the first extent in NVRAM. A reference to the first extent in NVRAM is stored in a first buffer header. The first buffer header is associated with the first process. The first process uses the first buffer header to directly access the one or more first data blocks in NVRAM.

Growing community of inventors

Sunnyvale, CA, United States of America

Kothanda Umamageswaran