Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Incremental Query Processing on Big Data Streams   This paper addresses online query processing for large-scale, incremental
data analysis on a distributed stream processing engine (DSPE). Our goal is to
convert any SQL-like query to an incremental DSPE program automatically. In
contrast to other approaches, we derive incremental programs that return
accurate results, not approximate answers. This is accomplished by retaining a
minimal state during the query evaluation lifetime and by using incremental
evaluation techniques to return an accurate snapshot answer at each time
interval that depends on the current state and the latest batches of data. Our
methods can handle many forms of queries on nested data collections, including
iterative and nested queries, group-by with aggregation, and equi-joins.
Finally, we report on a prototype implementation of our framework, called MRQL
Streaming, running on top of Spark and we experimentally validate the
effectiveness of our methods.

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The categories of this paper are: bayes-an
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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: q-alg
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The categories of this paper are: stat
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The categories of this paper are: supr-con
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The categories of this paper are: comp-gas
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The categories of this paper are: chem-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
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The categories of this paper are: quant-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: solv-int
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The categories of this paper are: math-ph