A survey on XML streaming evaluation techniques

Wu, Xiaoying; Theodoratos, Dimitri

doi:10.1007/s00778-012-0281-y

Cited by 21 publications

(11 citation statements)

References 69 publications

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“…This method combines the technique of projection for pre-filtering data which is irrelevant to query evaluation and the technique of dynamic garbage collection for automatic memory management. Other methods, for example, XEBT based on tree automaton [9] and the method of paper [27] based on pushdown automaton to deal with XPath query having complicate AND/OR sub-query.…”

Section: Stream-querying Algorithmsmentioning

confidence: 99%

An XML Streaming Data Processing Method based on Forest Transducer

He¹

2017

IJPE

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XML is the de facto standard for data representation and exchanging on web. The query processing technique of XML streaming data is a hotspot in current research. Focused on the characteristics of processing semi-structure XML streaming data such as the stream arriving continuously, requiring to be read sequentially and only once into memory, the querying must be processed on the fly, a method of processing XPath query based on forest transducer is proposed. Firstly, conversion rules of forest transducer are defined for XPath query. And then the transducer is driven by input streaming data nodes. Stack and abstract syntax tree are applied to implement match and state transformation in running procedure. The relationships between state functions and intermediate results are kept by the abstract syntax tree, and the query results are output in reducing process. Finally, the experimental results show that our approach is effective and efficient on this problem, and outperforms about 30 percent of the state-of-the-art algorithms especially for large processed data. At the same time, memory usage is nearly constant. This method resolves the balance between time and space complexity, and it is a useful reference for other methods.

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Section: Stream-querying Algorithmsmentioning

confidence: 99%

An XML Streaming Data Processing Method based on Forest Transducer

He¹

2017

IJPE

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“…It adopts the shortcut evaluation in the bottom-up path evaluation in order to identify whether candidate paths are matched to the query or not (lines [24][25][26][27][28][29][30]. Specifically, it immediately identifies p as not matched (lines 28 and 29), if a path from an element e to its closest ancestor query element e:ca 2 in p is not matched to the query (line 27).…”

Section: Algorithm 1 Xqstreammentioning

confidence: 99%

“…A comprehensive survey on query processing for streaming XML has been provided in [30], and various techniques [16,18,28] have been proposed to extract tuples from streaming XML. XSQ [28] deals with the streaming matching of XPath queries [9] with a single extraction node.…”

Section: Related Workmentioning

confidence: 99%

XQStream++: Fast tuple extraction algorithm for streaming XML data

Ryu

Lee

2015

Information Sciences

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“…XML stream processing systems [17,9,3] query XML data incrementally with a constant memory requirement. Instead of considering data parallelism, research on XML stream processing [33] has concentrated on increasing either the expressiveness of each query [16], or the number of queries that can be executed in a single run [37].…”

Section: Parallel Xpath Query Processingmentioning

confidence: 99%

Scalable XML query processing using parallel pushdown transducers

2013

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In online social networking, network monitoring and financial applications, there is a need to query high rate streams of XML data, but methods for executing individual XPath queries on streaming XML data have not kept pace with multicore CPUs. For data-parallel processing, a single XML stream is typically split into well-formed fragments, which are then processed independently. Such an approach, however, introduces a sequential bottleneck and suffers from low cache locality, limiting its scalability across CPU cores.We describe a data-parallel approach for the processing of streaming XPath queries based on pushdown transducers. Our approach permits XML data to be split into arbitrarilysized chunks, with each chunk processed by a parallel automaton instance. Since chunks may be malformed, our automata consider all possible starting states for XML elements and build mappings from starting to finishing states. These mappings can be constructed independently for each chunk by different CPU cores. For streaming queries from the XPathMark benchmark, we show a processing throughput of 2.5 GB/s, with near linear scaling up to 64 CPU cores.

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A survey on XML streaming evaluation techniques

Cited by 21 publications

References 69 publications

An XML Streaming Data Processing Method based on Forest Transducer

An XML Streaming Data Processing Method based on Forest Transducer

XQStream++: Fast tuple extraction algorithm for streaming XML data

Scalable XML query processing using parallel pushdown transducers

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