Amazon Technologies, Inc.

F5 Networks, Inc.

Andrew Whitaker

Sandeep Bhatia

Ming-Chuan Wu

Kanishka Chaturvedi

Maruthi Manohar Reddy Devarenti

VamsiKrishna Chaitanya Manchem

Peter John Godman

Pravin Mittal

Dhruv Goel

Stefano Stefani

David Alan Lutz

Yosseff Levanoni

Lucas Michael Kreger-Stickles

Mark Henry Oskin

Hao He

Andrew Michalski Schwerin

Lishi Jiang

Kaya Bekiroglu

Abhijeet More

Rajesh Iyer

Hong Yang

Nilanjan Basu

Abhilash Reddy Koppula

Nitin Ahuja

Kimi Shah

Pushap Goyal

Mark H Qskin

A non-relational database may be emulated using a relational database with a distributed data store. A request to access the non-relational database may be received at a frontend for a relational database engine that emulates an interface for a non-relational database engine. The request may be translated into the format for the relational database engine and performed by the relational database engine. The relational database engine may access data for the non-relational database at storage nodes that store the data in a relational table column of non-relational data type.

Emulating a non-relational database on a relational database with a distributed data store

Replicated partitions of a database may be moved from one or more replica nodes to a different primary node. The replica nodes may maintain replicated partitions of one or more primary partitions of a primary node servicing access requests to the primary partitions. The replicated partitions may be copied to a different node in order to cause the processing of access requests directed to primary partitions to be serviced by the different node. Replicated partitions of a database may be moved from replica nodes to perform a split operation or a merger operation.

Moving database partitions from replica nodes

Processing and storage responsibility for a data set may be split according to separately stored shards of the data set. As one or more loads associated with shards of the dataset grow a re-sharding operation may be performed to reduce loading of particular shards and nodes that host the particular shards. A re-sharding operation may cause only a sub-set of as set of shards of the dataset to be split and only cause second portions of the split shards to be stored in additional computing nodes. In some embodiments, a number of shards to be included in the sub-set of shards to be split may be selected based on an overall number of shards in the set and a largest number in the Fibonacci sequence that is less than the overall number of shards in the set.

Data re-sharding

A database testing system may generate, based on a randomization process, test data for a database. The system may generate a query that, when processed by the database, produces a first result that comprises the row. The system may modify the query based on a randomization process and in view of the semantic properties of the query language associated with the queries. The system may predict the outcome of the modifies query based on the semantic properties and on the generated test data. The system may verify that the modified query, when processed by the database, produces results consistent with the prediction.

Semantic-aware fuzz-based functional testing

Multi-type attribute indexes may be implemented for document databases. When a request to perform a query at a document database is received that is directed toward in indexed attribute that has multiple data types for values stored in the multi-type attribute index, a predicate in the query may be replaced with a different predicate that is applicable to search the multi-type attribute index according to a sort order for the multiple data types stored in the at multi-type attribute index. A plan that includes the different predicate may be performed in order to provide a result of the query to a user.

Multi-type attribute index for a document database

A distributed system may comprise a plurality of computing nodes, each of which may provide computing capacity for operating various computing services. The system may maintain a memory-based store of records representative of capacity available on the computing nodes. A record indicative of a computing node having a requested amount of capacity may be selected. The record may be modified to indicate that the computing node is a candidate for providing the requested amount of capacity. Upon receiving information confirming that the computing node has been configured to provide the requested capacity, the record may be modified to indicate that the computing node has committed to provide the requested capacity.

Cache-based partition allocation

Processing responsibility for a data set may be split according to separately stored partitions of the data set. A data set may be stored in different storage units that separately store different partitions of the data set. Mapping information may be maintained indicating the assignment of a node to process access requests to multiple partitions of a data set. A split event may be detected for the node, and one or more partitions assigned to the node may be reassigned to a different node. The storage units for the reassigned partitions may be made accessible to the different node. Then mapping information can be updated to indicate change in assignment from the original node to the different node so that the different node can begin processing access requests for the reassigned partitions.

Splitting processing responsibility for separately stored data partitions

A facility that for a multithreaded program executing on a root machine causes the threads of the program to be executed in a relative scheduling that produces an interesting result. The facility suspends execution of the program. The facility then tests a plurality of relative thread schedulings on one or more virtual machines and observes the result. Based upon the observed result the facility selects one of the tested relative thread schedulings. The facility then resumes execution of the program using the selected relative thread scheduling.

Automatic identification of interesting interleavings in a multithreaded program

A program code data structure is described. The data structure contains substantive code of a multithreaded computer program that includes a plurality of communicating instructions that effect communication between threads. The data structure further contains, at each of one or more points in the substantive code, an indication that, when the computer program is being executed, one or more communicating instructions that are in a selected relationship with the indication should be executed by any thread that reaches the point in a particular order relative to execution of one or more other communicating instructions by other threads. The contents of the data structure may be used to determine an order in which to execute communicating instructions.

Using hints to direct the exploration of interleavings in a multithreaded program

Growing community of inventors

Seattle, WA, United States of America

Andrew Whitaker