Progressive query computation using streaming architectures
First Claim
1. A method comprising:
- obtaining a relational query that references relational data items from a relational data table that lacks an explicit temporal attribute for ordering the relational data items of the relational data table;
adapting the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items, the explicit temporal data comprising different lifetimes;
providing the relational data items and the explicit temporal data as input events to the stream engine, wherein the stream engine performs a streaming query, corresponding to the relational query, on the input events using the different lifetimes to identify individual relational data items that contribute to corresponding incremental results of the streaming query;
obtaining the incremental results of the streaming query from the stream engine; and
outputting the incremental results.
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Accused Products
Abstract
The described implementations relate to processing of electronic data. One implementation is manifest as a technique that can include obtaining a relational query that references one or more data items and associating progress intervals with the data items. The technique can also include converting the relational query into a corresponding streaming query, and providing the streaming query and the data items with the progress intervals to a stream engine that produces incremental results of the query. For example, the progress intervals can be based on row numbers of a relational database table. The progress intervals can be used to define event lifetimes of streaming events that are provided as inputs to the stream engine.
58 Citations
20 Claims
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1. A method comprising:
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obtaining a relational query that references relational data items from a relational data table that lacks an explicit temporal attribute for ordering the relational data items of the relational data table; adapting the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items, the explicit temporal data comprising different lifetimes; providing the relational data items and the explicit temporal data as input events to the stream engine, wherein the stream engine performs a streaming query, corresponding to the relational query, on the input events using the different lifetimes to identify individual relational data items that contribute to corresponding incremental results of the streaming query; obtaining the incremental results of the streaming query from the stream engine; and outputting the incremental results. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system comprising:
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one or more processors; and one or more computer-readable storage media comprising instructions which, when executed by the one or more processors, cause the one or more processors to; obtain a relational query that references relational data items of a relational data table that lacks an explicit temporal attribute for ordering the relational data items of the relational data table; adapt the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items, the explicit temporal data comprising different lifetimes; provide the relational data items and the explicit temporal data as input events to the stream engine, the stream engine using the different lifetimes to identify individual relational data items that contribute to corresponding incremental results; and update an interface with the incremental results produced by the stream engine. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A system comprising:
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logic configured to; receive a first code entry that references rows of relational data items from of a relational data table that lacks an explicit temporal attribute for ordering the relational data items; receive a second code entry that relies on results of the first code entry; adapt the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items, the explicit temporal data comprising different lifetimes; provide input events comprising the relational data items and the explicit temporal data to a stream engine, the stream engine using the different lifetimes to identify individual relational data items that contribute to corresponding progressive results of the first code entry and the second code entry; and provide a visualization of the progressive results of the first code entry and the second code entry; and at least one processing device configured to execute the logic. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification