Google Inc.

Yahoo! Inc.

Excalibur Ip, LLC

Brian Frank Cooper

Sebastian Kanthak

Arif Abdulhusein Merchant

Alexander Shraer

Artyom Sharov

Alexander Lloyd

Utkarsh Srivastava

Ramana Yerneni

Andrew Fikes

Adam Silberstein

Iulian Moraru

Mert Akdere

Philip Lewis Bohannon

Daniel E Weaver

Raghu Ramakrishnan

Michael David Bigby

Christopher Scott Taylor

Raghunath Ramakrishnan

Jeffrey Terrace

Vadim Borisov

Benjamin Clay Reed

Erik Nathan Vee

Andrew Feng

Yang Zhang

Erwin Tam

Bryan Call

David Lomax

Christopher Taylor

Adam Eli Silberstein

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing clusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

Distributed database configuration

In a distributed database, a transaction is to be committed at a first coordinator server and one or more participant servers. The first coordinator server is configured to receive a notification that each participant server of the transaction is prepared at a respective prepared timestamp, the respective prepared timestamp being chosen within a time range for which the respective participant server obtained at least one lock. The first coordinator server computes the commit timestamp for the transaction equal or greater than each of the prepared timestamps, and restrict the commit timestamp such that a second coordinator server sharing at least one of the participant servers for one or more other transactions at a shared shard cannot select the same commit timestamp for any of the other transactions. The transaction is committed at the commit timestamp

Including transactional commit timestamps in the primary keys of relational databases

Systems and methods are provided for sending and receiving remote procedure calls (RPCs). Based on a message in a first RPC, a second set of RPCs are created by one or more computing devices, where each of the second set of RPCs includes a portion of the message in the first RPC. The message in the first RPC is replaced with a reference to each RPC of the second set of RPCs. The one or more computing devices send the first RPC with the references, and also send the second set of RPCs.

System and method for sending and receiving remote procedure calls

Methods and systems for monitoring performance in a distributed storage system described. One example method includes identifying requests sent by clients to the distributed storage system, each request including request parameter values for request parameters; generating probe requests based on the identified requests, the probe requests including probe request parameter values for probe request parameter values, representing a statistical sample of the request parameters included in the identified requests; sending the generated probe requests to the distributed storage system over a network, wherein the distributed storage system is configured to perform preparations for servicing each probe request in response to receiving the probe request; receiving responses to the probe requests from the distributed storage system, and outputting at least one performance metric value measuring a current performance state of the distributed storage system based on the received responses.

Performance monitoring in a distributed storage system

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing dusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

In a distributed system where a client's call to commit a transaction occurs outside the transaction's lock-hold interval, computation of timestamp information for the transaction is moved to a client library, while ensuring that no conflicting reads or writes are performed between a time of the computation and acquiring all locks for the transaction. The transaction is committed in phases, with each phase being initiated by the client library. Timestamp information is added to the locks to ensure that timestamps are generated during lock-hold intervals. An increased number of network messages is thereby overlapped with a commit wait period in which a write in a distributed database is delayed in time to ensure concurrency in the database.

Reducing commit wait in a distributed multiversion database by reading the clock earlier

Methods and systems for monitoring performance in a distributed storage system described. One example method includes identifying requests sent by clients to the distributed storage system, each request including request parameter values for request parameters; generating probe requests based on the identified requests, the probe requests including probe request parameter values for probe request parameter values, representing a statistical sample of the request parameters included in the identified requests; sending the generated probe requests to the distributed storage system over a network, wherein the distributed storage system is configured to perform preparations for servicing each probe request in response to receiving the probe request; receiving responses to the probe requests from the distributed storage system; and outputting at least one performance metric value measuring a current performance state of the distributed storage system based on the received responses.

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, the role of voting is assigned to a number of computing clusters. To make this selection, a task assigning service finds a candidate leader and M computing clusters to be used as voters. This selection may be based on finding latencies between the M computing clusters and the leader.

Distributed storage system with replica selection

Systems and methods are provided for efficiently sending large units of data in a network. A sender computing device splits the proposal into a plurality of fragments, and sends each of the plurality of fragments to a receiver computing device. The sender computing device receives an acknowledgement from the receiver computing device for each fragment received by the receiver computing device. If no acknowledgements for any fragments are received within a predetermined time period, it may be determined that an error occurred, in which case the sender may time out or take another action. The sender computing device further sends a message to the receiver computing device, wherein a payload of the message includes one or more references corresponding to the plurality of fragments sent.

System and method for sending proposals within a distributed state machine replication system

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, an indication that a number N of clusters are to be assigned a replica role and a second number M of the replica-role assigned clusters are to be assigned to a voting role. N computing clusters are selected using workload data, and M of the clusters are assigned to a voting role.

Distributed storage system with replica location selection

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San Jose, CA, United States of America

Brian Frank Cooper