Yahoo Assets LLC

Michael Pippin

Allie K Watfa

George Aleksandrovich

David Willcox

Jacob Tolar

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising processing a plurality of events using a stream processor and executing a deduplication process on the plurality of events using the stream processor. The plurality of events is outputted to a streaming queue and a close of books (COB) of a data transport is detected. Then, an audit process is initiated in response to detecting the COB signal, the audit process comprising comparing a set of raw events to a set of events in the streaming queue to identify a set of missing events, and replaying a set of missing events through the stream processor.

Duplicate detection and replay to ensure exactly-once delivery in a streaming pipeline

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving, at a stream processor, an event, the stream processor including a plurality of processing stages; generating, by the stream processor, an augmented event based on the event, the augmented event including at least one additional field not appearing in the event, the additional field generated by an operation selected from the group consisting of a join or dimensional annotation operation; and emitting, by the stream processor, the augmented event to downstream consumer.

Joining and dimensional annotation in a streaming pipeline

Techniques for providing batch performance using a stream processor are described. In one technique, a method includes receiving an event that includes an event key and a timestamp. The method then generates a partition value and time bucket value, the partition value generated based on the event key and the time bucket value generated based on the timestamp. The event key, partition value, and time bucket value are then combined to form a database key and used in a command to a database.

Partitioned backing store implemented in a distributed database

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising detecting a real close of books (COB) of a data transport, the real COB associated with a set of raw events transmitted over the data transport, flushing a stream processor in response to detecting the real COB, and retrieving a set of processed events from a distributed file system after the flushing is complete. A fact COB computation is then performed on the set of processed events and the set of raw events, the fact COB computation outputting a number of missing events, each missing event representing a raw event that is not present in the set of processed events. The processed events are then certified upon determining that the number of missing events is below a threshold.

Certifying events in a streaming pipeline

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving an event that includes a plurality of fields and extracting needed fields from the plurality of fields. The method then serializes the plurality of fields and generates a new event that includes the set of needed fields and a hidden field, the value of the hidden field comprising the serialized fields. The method then transmits the new event for processing using at least one processing stage of a stream processor. In response, the method reserializes a processed event generated by the stream processor and outputs the reserialized event to a downstream consumer.

Automatic schema upgrade in a big data pipeline

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving a stream of events, where each event comprises a header including an event type field and a timestamp. and identifying that the header of a given event in the stream of events includes at least one secondary event in a list of secondary identifiers included in the header. A flag is set in a distributed database for the at least one secondary event, then writing the given event to a table in the distributed database occurs, the table selected based on a respective event type field and timestamp associated with the given event. Deduplicating the given event and the at least one secondary event in response to a close of books (COB) signal occurs, after which writing at least one deduplicated event to a storage device occurs, the at least one deduplicated event selected from the group consisting of the given event and the at least one secondary event.

Exactly-once performance from a streaming pipeline in a fault-vulnerable system

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising completing a first audit for a primary event type, the first audit generating a set of primary events and completing a second audit for a secondary event type, the second audit generating a draft set of secondary events and an auxiliary feed of un-joined secondary events. The method then performs a join audit check on the auxiliary feed of un-joined secondary events and a set of flags, each flag in the set of flags indicating that a respective un-joined secondary event was properly joined. Based on the results of the join audit check, the method replays a subset of the un-joined secondary events in the auxiliary feed upon determining that the join audit check failed.

Parallel audit cycles between primary and secondary event feeds

Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a system is disclosed comprising a stream processor configured to process events emitted by an event stream and output processed events; a queue configured to receive the processed events from the stream processor; a spooler configured to read the processed events from the queue and write the processed events to a buffer; and an auditor process configured to extract a written event from the buffer and confirm that the written event matches an event present in the event stream.

Growing community of inventors

Sunnyvale, CA, United States of America

Michael Pippin