CN104102710A - Massive data query method - Google Patents
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- CN104102710A CN104102710A CN201410336964.3A CN201410336964A CN104102710A CN 104102710 A CN104102710 A CN 104102710A CN 201410336964 A CN201410336964 A CN 201410336964A CN 104102710 A CN104102710 A CN 104102710A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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Abstract
The invention discloses a massive data query method. The massive data query method is characterized by including establishing index mapping of query fields of non-rowkey value of Hbase (Hadoop database) and rowkey values; during query, inquiring the rowkey corresponding to the query fields in Solr Cloud according to the mapping relation; searching in the Hbase by the rowkey, and displaying query results in a paging manner.
Description
Technical field
The present invention relates to large data field, be specifically related to a kind of mass data inquiry method based on SolrCloud and HBase.
Background technology
Large data (Big data) are commonly used to a large amount of unstructured datas and the semi-structured data that describe that a company creates, these data download to relevant database can overspending time and money when analyzing.Normal and the cloud computing of large data analysis is linked together, because real-time large data set analysis need to share out the work to tens of, hundreds of or even thousands of computers by the framework as MapReduce, HBase.Large data analysis, than traditional data warehouse applications, has the features such as data volume is large, query analysis is complicated.Large data need special technology, effectively to process the data in a large amount of tolerance elapsed time.Be applicable to the technology of large data, comprise massively parallel processing (MPP) database, data mining electrical network, distributed file system, distributed data base, cloud computing platform, internet and extendible storage system.
Solr is an independently enterprise-level search application server, and it externally provides the api interface that is similar to Web-service.User can ask by http, submits the XML file of certain format to, generating indexes to search engine server; Also can propose search request by Http Get operation, and obtain returning results of XML or json form.SolrCloud is the distributed search scheme based on Solr and Zookeeper after Solr4.0 version.SolrCloud be Solr based on Zookeeper deployment way.
HBase be one distributed, towards row the database of increasing income, the Google paper " Bigtable: the distributed memory system of a structural data " that this Technology origin is write in Fay Chang.HBase – Hadoop Database is a high reliability, high-performance, towards row, telescopic distributed memory system, utilize HBase technology on cheap PC Server, to erect large-scale structure storage cluster.HBase, in providing high concurrent reading and writing operation to support, also exists some significant defects: because HBase only sorts to rowkey (line unit value), so HBase cannot realize fast finding and retrieval for field beyond rowkey.HBase also cannot realize Pagination Display and the inquiry page by page based on inquiry simultaneously.Therefore, design a kind of mass data inquiry method based on SolrCloud and HBase, can effectively address these problems.
Summary of the invention
In order to solve the problems of the technologies described above, the invention provides a kind of mass data inquiry method and device, realize many condition queries of mass data flexibly, the paging of fuzzy query and Query Result.
A kind of mass data inquiry method, comprising:
Set up the index-mapping of the non-line unit value of HBase rowkey inquiry field and rowkey;
When inquiry, according to described index-mapping relation, in SolrCloud, inquire rowkey corresponding to inquiry field;
Use described rowkey to search in HBase, and by Query Result Pagination Display.
Preferably, when the data in HBase change, the index-mapping in regular renewal SolrCloud.
Preferably, described index-mapping is distributed storage,
In the time of the renewal of master server reception hint mapping, the index-mapping of renewal is sent on other replica servers of same burst;
In the time of the renewal of replica server reception hint mapping, on the master server under the index-mapping of renewal is sent to.
Preferably, use Mapreduce model to accelerate the foundation of index-mapping.
A kind of mass data inquiry unit, comprising:
Mapping block, the index-mapping to the foundation of the non-rowkey inquiry of HBase field with rowkey;
Enquiry module according to index-mapping relation, first inquires the corresponding HBase rowkey of this inquiry field in SolrCloud, re-uses this rowkey and in HBase, inquires about required data;
Display module, by Query Result to user's Pagination Display.
Preferably, update module, in the time of data change in HBase, the index-mapping in regular renewal SolrCloud.
Preferably, synchronization module,, sends to the index-mapping of renewal on other replica servers of same burst during as master server at this device.
Preferably, synchronization module, at this device during as replica server, after update module is upgraded index-mapping, on the master server under synchronization module sends to the index-mapping of renewal.
The application's technical scheme is used the non-rowkey field of the needs inquiry in SolrCloud storage and maintenance HBase to the index-mapping of rowkey, find corresponding rowkey according to querying condition, re-use rowkey and in HBase, carry out searching of data, thereby many condition queries of mass data are flexibly realized, the paging of fuzzy query and Query Result; Meanwhile, SolrCloud adopts distributed way to dispose, and can realize centralized information storage, automatic fault tolerant, nearly real-time search and automatically load balancing.
Brief description of the drawings
Accompanying drawing described herein is used to provide a further understanding of the present invention, forms the application's a part, and schematic description and description of the present invention is used for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the Solr+HBase inquiry schematic diagram of the embodiment of the present invention;
Fig. 2 is the HBase rowkey index-mapping schematic diagram of the embodiment of the present invention;
Fig. 3 is the SolrCloud cluster distribution schematic diagram of the embodiment of the present invention;
Fig. 4 is the mass data inquiry method process flow diagram of the embodiment of the present invention;
Fig. 5 is the mass data inquiry unit structural drawing of the embodiment of the present invention.
Embodiment
The present invention adopts the method based on SolrCloud+HBase, can be to the non-rowkey field foundation of the appointment in HBase and the index-mapping of rowkey, when inquiry, first find the rowkey corresponding to field that will inquire about, then in HBase, search the single problem of querying condition while having avoided HBase directly to inquire about.The present invention is showing when Query Result, can Pagination Display; Thereby the many condition queries and the Query Result paging that provide convenience easily to realize provide traditional HBase to store not available full-text index, the ability of fuzzy query simultaneously.For the request of quantity statistics class, directly can obtain result by the index-mapping of Solr, needn't carry out inquiry request to HBase again.
Below in conjunction with drawings and the specific embodiments, the present invention is described in detail.
Every record in HBase carries out Ordered indices according to rowkey, and the mode of its index, as described in Fig. 2, is the form of a multiple index, adopts the location that is similar to 3 layers of B+ tree.First be the position of finding root region place from zookeeper, thereby loading-ROOT-is this region.-ROOT-region is first region of .META. table, and the positional information of other all region of .META. table has been deposited in the inside.And .META. table is to reside in the internal memory of all RegionServer, wherein depositing the region positional information of all tables of data.In the time inquiring about in HBase by rowkey, exactly by search-ROOT-, then .META. navigates to the region at data place, then from this region, takes out valid data.Because the index of each step is all that established and orderly, be very high so use this search efficiency based on rowkey in HBase.But for the inquiry of non-rowkey, efficiency just significantly declines.
In order to address this problem, the present invention uses SolrCloud in advance non-rowkey inquiry field to be set up a group index mapping of its corresponding rowkey, query script as shown in Figure 1, first in SolrCloud, inquire the corresponding HBase rowkey of this querying condition, re-use this rowkey data query in HBase, finally, return to Query Result to client.This mode can improve search efficiency greatly.
SolrCloud adopts distributed way to dispose, and can realize centralized information storage, automatic fault tolerant, nearly real-time search and automatically load balancing.As shown in Figure 3, this is a SolrCloud cluster that has 6 nodes (server), index-mapping is distributed in two Shard (burst) the inside, each Shard comprises three Solr nodes, a Leader (master) node, two Replica (copy) node.There are 3 copies in each Shard, in the time that 2 nodes are delayed machine simultaneously, system still can normally be worked simultaneously.All status informations of cluster are safeguarded by Zookeeper cluster is unified.For these 6 nodes, any one node can be accepted the update request of index-mapping, thereby has realized load balancing.For example, when this node of Server4 has been received the update request about Shard1 index-mapping, Server4 can be transmitted to information that Leader node, i.e. Server1 that index-mapping should be affiliated.After Server1 node updates finishes, version number and index-mapping are issued to other Replicas nodes that belong to a Shard, i.e. Server2 and Server3, completes synchronous.
Mass data inquiry method provided by the invention, as shown in Figure 4, comprising:
Step 401, the index-mapping to the foundation of the non-rowkey inquiry of HBase field with rowkey.
In the time that the data of HBase are set up, according to the querying condition arranging, use SolrCloud to set up the index-mapping of non-rowkey field and rowkey.Described querying condition arranges for the non-rowkey field of HBase.
In the stage of setting up at Solr index-mapping, can use Mapreduce model to accelerate the foundation of index-mapping.
Step 402 when inquiry, according to index-mapping relation, inquires corresponding rowkey in SolrCloud.
In the time that needs are inquired about, according to index-mapping relation, first in SolrCloud, inquire the corresponding HBase rowkey of this querying condition, re-use this rowkey and in HBase, inquire about required data.
Preferably, described index-mapping is distributed storage,
In the time of the renewal of master server reception hint mapping, the index-mapping of renewal is sent on other replica servers of same burst;
In the time of the renewal of replica server reception hint mapping, on the master server under the index-mapping of renewal is sent to.
Step 403, by Query Result to user's Pagination Display.
Obtain in HBase according to rowkey after data, while demonstration to user, according to the paging mode arranging, show to user.
In the original mode of HBase, Query Result is not supported Pagination Display, and user can only all check Query Result.And improvement of the present invention is, for example, to Query Result Pagination Display: every page shows 20, and user can be very clear to shown project.
Preferably, the method can also comprise: in the time of data change in HBase, and the index-mapping in regular renewal SolrCloud.
The present invention also provides corresponding mass data inquiry unit, as shown in Figure 5, comprising:
Mapping block, the index-mapping to the foundation of the non-rowkey inquiry of HBase field with rowkey;
Enquiry module according to index-mapping relation, first inquires the corresponding HBase rowkey of this querying condition in SolrCloud, re-uses this rowkey and in HBase, inquires about required data;
Display module, by Query Result to user's Pagination Display.
Preferably, this device also comprises update module, in the time of data change in HBase, and the index-mapping in regular renewal SolrCloud.
Mass data inquiry unit of the present invention can be used as a server node, as shown in Figure 3, in each server, can arrange, and forms a cluster.
Preferably, returning apparatus also comprises synchronization module, at this device during as replica server, after update module is upgraded index-mapping, on the master server under synchronization module sends to the index-mapping of renewal.
Preferably, synchronization module,, sends to the index-mapping of renewal on other replica servers of same burst during as master server at this device.
Application Example
Definition and the configuration of 1.Solr schema (framework) file
Amendment schema.xml file, adds the field that needs index therein.Revise original uniqueKey simultaneously, the uniqueKey that the rowkey in HBase table is Solr is set.
2. the foundation of index-mapping
By the mode of the full table scan of HBase API (Scan) or by the mode of MapReduce, the data in HBase are set up to Solr index.
3. the realization of inquiry and paging
When inquiry, in Solr, find querying condition corresponding one or one group of rowkey.After having obtained these rowkey, the use rowkey of grouping inquires about in HBase, thereby inquires actual result and realized paging and searched.
One of ordinary skill in the art will appreciate that all or part of step in said method can carry out instruction related hardware by program and complete, described program can be stored in computer-readable recording medium, as ROM (read-only memory), disk or CD etc.Alternatively, all or part of step of above-described embodiment also can realize with one or more integrated circuit.Correspondingly, the each module/unit in above-described embodiment can adopt the form of hardware to realize, and also can adopt the form of software function module to realize.The application is not restricted to the combination of the hardware and software of any particular form.
The above, be only preferred embodiments of the present invention, is not intended to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any amendment of making, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (8)
1. a mass data inquiry method, is characterized in that, comprising:
Set up the index-mapping of the non-line unit value of HBase rowkey inquiry field and rowkey;
When inquiry, according to described index-mapping relation, in SolrCloud, inquire rowkey corresponding to inquiry field;
Use described rowkey to search in HBase, and by Query Result Pagination Display.
2. the method for claim 1, is characterized in that,
When data in HBase change, the index-mapping in regular renewal SolrCloud.
3. method as claimed in claim 2, is characterized in that,
Described index-mapping is distributed storage,
In the time of the renewal of master server reception hint mapping, the index-mapping of renewal is sent on other replica servers of same burst;
In the time of the renewal of replica server reception hint mapping, on the master server under the index-mapping of renewal is sent to.
4. the method for claim 1, is characterized in that,
Use Mapreduce model to accelerate the foundation of index-mapping.
5. a mass data inquiry unit, is characterized in that, comprising:
Mapping block, the index-mapping to the foundation of the non-rowkey inquiry of HBase field with rowkey;
Enquiry module according to index-mapping relation, first inquires the corresponding HBase rowkey of this inquiry field in SolrCloud, re-uses this rowkey and in HBase, inquires about required data;
Display module, by Query Result to user's Pagination Display.
6. device as claimed in claim 5, is characterized in that, also comprises:
Update module, in the time of data change in HBase, the index-mapping in regular renewal SolrCloud.
7. device as claimed in claim 5, is characterized in that, also comprises:
Synchronization module,, sends to the index-mapping of renewal on other replica servers of same burst during as master server at this device.
8. device as claimed in claim 7, is characterized in that,
Synchronization module, at this device during as replica server, after update module is upgraded index-mapping, on the master server under synchronization module sends to the index-mapping of renewal.
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