Amazon Technologies, Inc.

Vijay Gopal Joshi

Gaurav D Ghare

Sayantan Chakravorty

Mushegh Malkhasyan

Babu Prasad Dhandapani

Jeremiah Wilton

Balakrishnan Narayanaswamy

Qia Wang

Maxym Kharchenko

Artem Kryvokrysenko

Zhao Song

Kyle Henderson Hailey

Hefeng Chen

Duc Viet Nguyen

Joshua Tobey Oberwetter

Siva Somasundaram

Mitchell Ross Loeppky

Vikramank Yogendra Singh

An anomalous period of operation of a database management system is detected by analyzing a time series of data points indicating the number of database queries pending processing by the system. Conditions associated with execution of the pending database queries are recorded and analyzed to identify conditions correlated with the anomalous period of operation. A recommendation for tuning the database is generated based on analysis of the conditions.

Assisted database anomaly mitigation

Disclosed are various embodiments for consuming fragments of time-associated data streams. A streaming gateway receives a request from a consumer via a network to obtain a stream of time-associated data. The gateway determines that a first fragment of the stream of time-associated data is stored in a data store. The first fragment is obtained from the data store and sent to the consumer via the network. The gateway determines that the stream of time-associated data is currently being received by an endpoint from a producer. A second segment of the stream is obtained from the endpoint and sent to the consumer via the network.

Consuming fragments of time-associated data streams

Techniques for estimating speed for an object in a video (either stream or file) are described. In particular, once an object has been recognized, additional data (such as size) for that recognized object is used in a determination of a 3D position of that object in a plurality of frames. An estimated speed may be found using a difference between 3D positions of the object in different frames over the time between the frames.

Moving object recognition, speed estimation, and tagging

Disclosed are various embodiments for fragmentation of time-associated streaming data. A producer application receives a stream of time-associated data. The producer application then generates a first fragment of the stream of time-associated data and assigns a first unique fragment identifier and a first timestamp to the first fragment. The producer application sends the first fragment via a network using an application-layer protocol to an endpoint. The producer application receives at least one acknowledgement for the first fragment from the endpoint via the network using the application-layer protocol.

Fragmentation of time-associated data streams

Various embodiments replicate and index fragments of a stream of time-associated data. In one embodiment, a stream endpoint application receives a first fragment of a stream of time-associated data from a producer via a network using an application-layer protocol. The stream endpoint application determines a producer timestamp from the first fragment. The stream endpoint application sends at least one acknowledgment to the producer via the network using the application-layer protocol. The stream endpoint application indexes the first fragment and sends the first fragment to a destination.

Replicating and indexing fragments of time-associated data streams

Growing community of inventors

Bellevue, WA, United States of America

Vijay Gopal Joshi