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Hybrid indexing method based on big-data model metadata

A metadata and big data technology, applied in the field of hybrid indexing based on big data model metadata, to achieve the effect of improving retrieval speed and increasing convenience

Active Publication Date: 2017-10-20
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a hybrid indexing method based on big data model metadata, which can solve the problem of model retrieval and management under the big data model comprehensive analysis platform

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  • Hybrid indexing method based on big-data model metadata
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  • Hybrid indexing method based on big-data model metadata

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Embodiment 1

[0033] Such as figure 1 and Figure 4 As shown, a hybrid index structure based on big data model metadata includes the following steps:

[0034] S1: Extract the mixed index metadata, extract the metadata for constructing the mixed index according to the big data model metadata and model interpretation and operation characteristics, and assign 1 or 0 to the metadata attribute according to the interpretation and operation characteristics of the big data model;

[0035] S2: Construct or update a hybrid index, construct or update a hybrid index for the submission of big data model records by constructing a global hash function according to the extracted metadata and metadata attribute values;

[0036] S3: Store the hybrid index. According to the characteristics of the hybrid index, store each part of the hybrid index in memory, cache, and external memory (disk), and retrieve the contents of the index in parallel according to the query requirements;

[0037] S4: Retrieve the hybr...

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Abstract

The invention discloses a hybrid indexing method based on big-data model metadata. The method comprises the following steps: S1, extracting hybrid index metadata, wherein the metadata of a hybrid index is extracted according to the big-data model metadata and model interpretation and operation characteristics, and a value of 1 or 0 is assigned to the metadata according to an attribute value of the metadata; S2, constructing or updating the hybrid index, wherein a global hash function is utilized to construct or update the hybrid index; S3, storing the hybrid index, wherein all parts of the hybrid index are stored into a memory, a cache and a disk according to hybrid index features, and index contents are sequentially and concurrently retrieved according to a query request; and S4, retrieving the hybrid index, wherein a retrieval algorithm is constructed according to big-data model features and hybrid index characteristics, and the different parts of the hybrid index are retrieved at the same time. According to the method, the big-data model metadata and the model characteristics are tightly integrated, a high-efficient and accurate model indexing technology is provided, the retrieval speed is increased, and the convenience of big-data model using is improved.

Description

technical field [0001] The invention relates to a hybrid index method, in particular to a hybrid index method based on big data model metadata. Background technique [0002] With the emergence of cloud computing, distributed clusters and big data research, the original relational databases and indexes are gradually unable to meet the current network and computing requirements, especially the consistency of relational databases has become less important, which requires The emergence of new data storage methods and indexing methods. In 2009, a discussion about open source distributed database led to the emergence of NoSQL. With the open source of Google's distributed file system and BigTable, non-relational databases have received attention, research and application at home and abroad. [0003] Different from relational databases, non-relational databases propose another record storage and management method, for example, stored in key-value pairs, and the structure is not fix...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9014G06F16/9027
Inventor 林劼张译权李年华王芷若王勇
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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