CN108509438A - A kind of ElasticSearch fragments extended method - Google Patents
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Abstract
The invention discloses a kind of ElasticSearch fragments extended methods, computer big data index technology field, one is needed the tables of data divided to create an expansion table by the present invention, the data for the fragment that needs are divided are more parts according to certain regular cutting, portion is stayed in original fragment, other imported into the correspondence fragment of expansion table, solve when a fragment data amount is excessive, ES does not have the problem of function of dividing automatically, improves inquiry and the warehouse-in efficiency of data.
Description
Technical field
The invention belongs to computer big data index technology fields.
Background technology
In current full-text search, Lucene is the most simple and convenient, and Lucene is a full text information retrieval kit, uses
Be inverted file index structure.Its not instead of complete search for application, index is provided for your application program
And function of search.Full-text index/the search function realized in various applications for application can be easily embedded into.Currently, with
Clustering based on Lucene includes mainly Solr and Elasticsearch (abbreviation ES below),
ElasticSearch is a search server based on Lucene.It provides the full text of a distributed multi-user ability
Search engine supports RESTful web, java interfaces, can support to search in real time have and stablize, reliably, quickly, installation makes
The features such as with facilitating.
Fragment is the basic storage cell of each index data table of ES, and bottom is a Lucene storage catalogue, can be with
It is distributed to different memory nodes, when a fragment data amount is excessive, ES does not have the function of dividing automatically, at this time can
The inquiry of reduction system and warehouse-in efficiency.
Invention content
The object of the present invention is to provide a kind of ElasticSearch fragments extended method, solve when a fragment data
When measuring excessive, ES does not have the problem of function of dividing automatically, improves inquiry and the warehouse-in efficiency of data.
To achieve the above object, the present invention uses following technical scheme：
A kind of ElasticSearch fragments extended method, includes the following steps：
Step 1：Full-text index system is established, full-text index system includes Hadoop storage servers cluster, WEB interface clothes
Device, the data of being engaged in import server and data collection station, and data collection station connects data by internet and imports server,
WEB interface server imports server with data and connects Hadoop storage server clusters by internet；
Step 2：By Lucene full text information retrievals tool full-text search is established in Hadoop storage server clusters
Platform, and ES clusters are distributed in Hadoop storage server clusters by Lucene full text information retrievals tool；
Step 3：Flow data or text data are input to data and import server, the data service of pouring by data collection station
Flow data or text data are sent to Hadoop storage server clusters and stored by device；
Step 4：ES clusters pass through the number that Lucene full text information retrieval tools are Hadoop storage server cluster-based storages
According to the index data table for establishing inverted file index structure, ES clusters provide the field area of storage for index data table；It is described
In the field area of storage field area is stored comprising multiple number of documents；
ES clusters provide the field area of storage for index data table according to the following steps：
Step S1：Setting fragment is the basic storage cell of each index data table, each index data table wraps
Containing several fragments, ES clusters store index data table distribution storage to the difference in ES clusters according to the fragment of index data table
In medium；
Step S2：Index lists are set as an index data table in ES clusters, shard fragments are index lists
One fragment；Include multiple shard fragments in index lists；Set a fragmentation threshold；
Step S3：ES clusters establish an extension index list to index lists, and ES clusters are read in index lists most
Big shard fragments, judge whether shard fragments reach fragmentation threshold：It is to then follow the steps S4, it is no, then follow the steps S5；
ES clusters are established an extension index list to index lists and are as follows：
Step A：ES clusters obtain index lists, and traverse each shard fragment in index lists, and do following
Judge：If shard fragments exceed fragmentation threshold, C is thened follow the steps；If shard fragments are thened follow the steps without departing from fragmentation threshold
B；
Step B：Whether the fragment of the expansion table under inquiry shard fragments has beyond fragmentation threshold：It is to then follow the steps C；
It is no, then follow the steps S4；
Step C：ES clusters according to the size of fragmentation threshold be calculated over fragmentation threshold shard fragments should cutting
Whether number, the shard fragments that verification extension index lists whether there is or extend index lists have expired：If be not present or
Shard fragments have been expired, then continue to extend new extension index lists, and shard fragment numbers are existing shard fragments
Twice of number, in newly-increased extension index form informations update to routing table；If in the presence of had more than fragment is listed
The shard fragment lists of threshold value, and be added in the task queue of Zookeeper after descending arrangement；The task team of Zookeeper
Row generate multiple job tasks according to shard fragment lists；
Step S4：Shard fragments are divided according to following steps：
Step D：For ES clusters after obtaining a job task in the task queue of Zookeeper, notice Ares is put in storage journey
Sequence stops carrying out in-stockroom operation to the table, judges that Ares enters whether library returns to message：It is to then follow the steps E；It is no, then etc.
Wait for that Ares enters library response；
Step E：ES clusters are started to carry out splitting operation to shard fragments by following rule：
Step E1：ES clusters obtain the storage size of the shard fragments；
Step E2：Fragment result of calculation will be obtained behind the storage size divided by 2, by fragment result of calculation and fragmentation threshold
It compares：If it is greater than fragmentation threshold, the storage size divided by 2 times N are executed step E2 by record；If it is less than point
Piece threshold value, 2 × N of record are the number to be divided；
Step E3：The total amount of data total for obtaining the shard fragments, the data volume size K after division：K=total ÷
(2×N)；
Step E4：A time T is given by ES cluster query interfaces, T unit is the second, when the data note obtained in T seconds
Size for m, coefficient value s, s is equal to K ÷ m；ES clusters are according to s pairs of the number of the division, data volume size K and coefficient
Shard fragments are into line splitting；
Step F：New fragment after ES clusters divide shard fragments is numbered, set the number of new fragment as
Shard [0] fragment；
Step G：The data in shard fragments are deleted, the data in shard [0] fragment are substituted into the number in shard fragments
According to, and the shard of information [0] fragment is added in index lists；Simultaneously will in shard fragments except shard [0] fragments with
Outer fragment is written in the shared catalogues of NFS, and extends the fragment of index lists, and dividing in the catalogue shared according to NFS
It, will be more than the shard of fragmentation threshold again according to the method for step C after piece does recovery recoveries to the fragment of index lists
Fragment list, and be added in the task queue of Zookeeper after descending arrangement；
Step H：The flow path track for recording splitting operation, and updates in flow path track to routing table, and routing table is according to newly
Flow path track generates new routing rule, and data are put in storage or are inquired according to new routing rule by ES clusters；
Step S5：Fragment extension terminates, and repeats step S1 to step S4, until ES clusters are all index lists
It is provided which the field area of storage.
The ES clusters are Elasticsearch server clusters.
The data collection station is 10,000,000,000 interchangers.
A kind of ElasticSearch fragments extended method of the present invention is solved when a fragment data amount is excessive
When, ES does not have the problem of function of dividing automatically, improves inquiry and the warehouse-in efficiency of data；The fragment that the present invention uses point
The method split can be stepped up the extended capability of system, cause after avoiding data volume from reaching certain rank ES clusters storage with
The performance of retrieval declines.
Description of the drawings
Fig. 1 is the overview flow chart of the present invention；
Fig. 2 is the flow chart of the step S3 of the present invention；
Fig. 3 is the flow chart of the step S4 of the present invention.
Specific implementation mode
A kind of ElasticSearch fragments extended method as shown in FIG. 1 to 3, includes the following steps：
Step 1：Full-text index system is established, full-text index system includes Hadoop storage servers cluster, WEB interface clothes
Device, the data of being engaged in import server and data collection station, and data collection station connects data by internet and imports server,
WEB interface server imports server with data and connects Hadoop storage server clusters by internet；
Step 2：By Lucene full text information retrievals tool full-text search is established in Hadoop storage server clusters
Platform, and ES clusters are distributed in Hadoop storage server clusters by Lucene full text information retrievals tool；
Step 3：Flow data or text data are input to data and import server, the data service of pouring by data collection station
Flow data or text data are sent to Hadoop storage server clusters and stored by device；
Step 4：ES clusters pass through the number that Lucene full text information retrieval tools are Hadoop storage server cluster-based storages
According to the index data table for establishing inverted file index structure, ES clusters provide the field area of storage for index data table；It is described
In the field area of storage field area is stored comprising multiple number of documents；
ES clusters provide the field area of storage for index data table according to the following steps：
Step S1：Setting fragment is the basic storage cell of each index data table, each index data table wraps
Containing several fragments, ES clusters store index data table distribution storage to the difference in ES clusters according to the fragment of index data table
In medium；
Step S2：Index lists are set as an index data table in ES clusters, shard fragments are index lists
One fragment；Include multiple shard fragments in index lists；Set a fragmentation threshold；
Step S3：ES clusters establish an extension index list to index lists, and ES clusters are read in index lists most
Big shard fragments, judge whether shard fragments reach fragmentation threshold：It is to then follow the steps S4, it is no, then follow the steps S5；
ES clusters establish the premise of an extension index list to index lists, and to be index lists have alias, the extension index of foundation
List has same alias, and the shard fragments number for extending index lists is identical as index lists.
ES clusters are established an extension index list to index lists and are as follows：
Step A：ES clusters obtain index lists, and traverse each shard fragment in index lists, and do following
Judge：If shard fragments exceed fragmentation threshold, C is thened follow the steps；If shard fragments are thened follow the steps without departing from fragmentation threshold
B；
Step B：Whether the fragment of the expansion table under inquiry shard fragments has beyond fragmentation threshold：It is to then follow the steps C；
It is no, then follow the steps S4；
Step C：ES clusters according to the size of fragmentation threshold be calculated over fragmentation threshold shard fragments should cutting
Whether number, the shard fragments that verification extension index lists whether there is or extend index lists have expired：If be not present or
Shard fragments have been expired, then continue to extend new extension index lists, and shard fragment numbers are existing shard fragments
Twice of number, in newly-increased extension index form informations update to routing table；If in the presence of had more than fragment is listed
The shard fragment lists of threshold value, and be added in the task queue of Zookeeper after descending arrangement；The task team of Zookeeper
Row generate multiple job tasks according to shard fragment lists；
Step S4：Shard fragments are divided according to following steps：
Step D：For ES clusters after obtaining a job task in the task queue of Zookeeper, notice Ares is put in storage journey
Sequence stops carrying out in-stockroom operation to the table, judges that Ares enters whether library returns to message：It is to then follow the steps E；It is no, then etc.
Wait for that Ares enters library response；
Step E：ES clusters are started to carry out splitting operation to shard fragments by following rule：
Step E1：ES clusters obtain the storage size of the shard fragments；
Step E2：Fragment result of calculation will be obtained behind the storage size divided by 2, by fragment result of calculation and fragmentation threshold
It compares：If it is greater than fragmentation threshold, the storage size divided by 2 times N are executed step E2 by record；If it is less than point
Piece threshold value, 2 × N of record are the number to be divided；
Step E3：The total amount of data total for obtaining the shard fragments, the data volume size K after division：K=total ÷
(2×N)；
Step E4：A time T is given by ES cluster query interfaces, T unit is the second, when the data note obtained in T seconds
Size for m, coefficient value s, s is equal to K ÷ m；ES clusters are according to s pairs of the number of the division, data volume size K and coefficient
Shard fragments are into line splitting；
Step F：New fragment after ES clusters divide shard fragments is numbered, set the number of new fragment as
Shard [0] fragment；
Step G：The data in shard fragments are deleted, the data in shard [0] fragment are substituted into the number in shard fragments
According to, and the shard of information [0] fragment is added in index lists；Simultaneously will in shard fragments except shard [0] fragments with
Outer fragment is written in the shared catalogues of NFS, and extends the fragment of index lists, and dividing in the catalogue shared according to NFS
It, will be more than the shard of fragmentation threshold again according to the method for step C after piece does recovery recoveries to the fragment of index lists
Fragment list, and be added in the task queue of Zookeeper after descending arrangement；
Step H：The flow path track for recording splitting operation, and updates in flow path track to routing table, and routing table is according to newly
Flow path track generates new routing rule, and data are put in storage or are inquired according to new routing rule by ES clusters；
Step S5：Fragment extension terminates, and repeats step S1 to step S4, until ES clusters are all index lists
It is provided which the field area of storage.
The ES clusters are Elasticsearch server clusters.
The data collection station is 10,000,000,000 interchangers.
In use, specific ES fragments extension uses Master-Slave structures, pass through tables of data dependent on zookeeper
(Index) fragment list generates multiple operations, and each these operations of division module schedules execute operation, complete division fragment
(Shard) operation.ZooKeeper is one distributed, and the distributed application program coordination service of open source code is
Mono- realization increased income of Chubby of Google, is the significant components of Hadoop and Hbase.
ES fragments extend the service condition for capableing of each fragment of dynamic monitoring, and the action of fragment division can be among the nodes
Dynamically mobile data, and ensure the dynamic equilibrium of each node, while the speed handled is very fast.If extended in fragment
When there are abnormal conditions, then be included in failed tasks at once, the function of data convert done for original fragment, and can
Automatically the task by failure is redistributed.
The data collection station is 10,000,000,000 interchangers, and 10,000,000,000 interchangers can obtain a large amount of data source from internet,
The format of data source is data file and stream data；
ES clusters provide data loading, query analysis and management and monitoring interface, storage to Hadoop storage server clusters
Medium is local disk, and ES clusters support various Spark components；WEB interface server passes through Zues-client and Loki and ES
Cluster docks；
Zues-client is the ES interfaces encapsulated, is called for upper layer；Loki is the inquiry middleware of unified index, is responsible for
The structural data, unstructured data, blended data inquiry request of upper-layer user are received, analysis cutting forwards the request to ES,
And data are obtained from structural data system, unstructured data system according to the data id of return.
A kind of ElasticSearch fragments extended method of the present invention is solved when a fragment data amount is excessive
When, ES does not have the problem of function of dividing automatically, improves inquiry and the warehouse-in efficiency of data；The fragment that the present invention uses point
The method split can be stepped up the extended capability of system, cause after avoiding data volume from reaching certain rank ES clusters storage with
The performance of retrieval declines.
Claims (3)
1. a kind of ElasticSearch fragments extended method, it is characterised in that：Include the following steps：
Step 1：Full-text index system is established, full-text index system includes Hadoop storage servers cluster, WEB interface service
Device, data import server and data collection station, and data collection station connects data by internet and imports server, WEB
Interface server imports server with data and connects Hadoop storage server clusters by internet；
Step 2：Full-text search platform is established in Hadoop storage server clusters by Lucene full text information retrievals tool,
And ES clusters are distributed in Hadoop storage server clusters by Lucene full text information retrievals tool；
Step 3：Flow data or text data are input to data and import server by data collection station, and data pour into server will
Flow data or text data are sent to Hadoop storage server clusters and are stored；
Step 4：ES clusters are built by the data that Lucene full text information retrieval tools are Hadoop storage server cluster-based storages
The index data table of vertical inverted file index structure, ES clusters provide the field area of storage for index data table；The storage
In field area field area is stored comprising multiple number of documents；
ES clusters provide the field area of storage for index data table according to the following steps：
Step S1：Setting fragment is the basic storage cell of each index data table, if each index data table includes
Dry fragment, ES clusters store the distribution of index data table to the different storage mediums in ES clusters according to the fragment of index data table
In；
Step S2：Index lists are set as an index data table in ES clusters, shard fragments are one of index lists
Fragment；Include multiple shard fragments in index lists；Set a fragmentation threshold；
Step S3：ES clusters establish an extension index list to index lists, and ES clusters read maximum in index lists
Shard fragments, judge whether shard fragments reach fragmentation threshold：It is to then follow the steps S4, it is no, then follow the steps S5；
ES clusters are established an extension index list to index lists and are as follows：
Step A：ES clusters obtain index lists, and traverse each shard fragment in index lists, and do and following sentence
It is disconnected：If shard fragments exceed fragmentation threshold, C is thened follow the steps；If shard fragments then follow the steps B without departing from fragmentation threshold；
Step B：Whether the fragment of the expansion table under inquiry shard fragments has beyond fragmentation threshold：It is to then follow the steps C；It is no,
Then follow the steps S4；
Step C：ES clusters according to the size of fragmentation threshold be calculated over fragmentation threshold shard fragments should cutting number,
Whether the shard fragments that verification extension index lists whether there is or extend index lists have expired：If being not present or shard dividing
Piece has been expired, then continues to extend new extension index lists, and shard fragment numbers are the two of the number of existing shard fragments
Times, in newly-increased extension index form informations update to routing table；If in the presence of had more than fragmentation threshold is listed
Shard fragment lists, and be added in the task queue of Zookeeper after descending arrangement；The task queue of Zookeeper according to
Shard fragment lists generate multiple job tasks；
Step S4：Shard fragments are divided according to following steps：
Step D：After obtaining a job task in the task queue of Zookeeper, notice Ares enters library and stops ES clusters
In-stockroom operation only is carried out to the table, judges that Ares enters whether library returns to message：It is to then follow the steps E；It is no, then it waits for
Ares enters library response；
Step E：ES clusters are started to carry out splitting operation to shard fragments by following rule：
Step E1：ES clusters obtain the storage size of the shard fragments；
Step E2：Fragment result of calculation will be obtained behind the storage size divided by 2, by fragment result of calculation compared with fragmentation threshold
Compared with：If it is greater than fragmentation threshold, the storage size divided by 2 times N are executed step E2 by record；If it is less than fragment threshold
Value, 2 × N of record is the number to be divided；
Step E3：The total amount of data total for obtaining the shard fragments, the data volume size K after division：K=total ÷ (2 ×
N)；
Step E4：A time T is given by ES cluster query interfaces, T unit is the second, and when T seconds, the interior data obtained were denoted as m,
Coefficient value is s, and the size of s is equal to K ÷ m；ES clusters are according to the number of the division, data volume size K and coefficient s to shard
Fragment is into line splitting；
Step F：New fragment after ES clusters divide shard fragments is numbered, and sets the number of new fragment as shard
[0] fragment；
Step G：The data in shard fragments are deleted, the data in shard [0] fragment are substituted into the data in shard fragments,
And the shard of information [0] fragment is added in index lists；Simultaneously by shard fragments in addition to shard [0] fragment
Fragment is written in the shared catalogues of NFS, and extends the fragment of index lists, and according to the fragment pair in catalogue shared NFS
It, will be more than the shard fragments of fragmentation threshold again according to the method for step C after the fragment of index lists does recovery recoveries
List, and be added in the task queue of Zookeeper after descending arrangement；
Step H：The flow path track of splitting operation is recorded, and is updated in flow path track to routing table, routing table is according to new flow
Data are put in storage or are inquired according to new routing rule by the new routing rule of Track Pick-up, ES clusters；
Step S5：Fragment extension terminates, and repeats step S1 to step S4, until ES clusters are that all index lists carry
For the field area of storage.
2. a kind of ElasticSearch fragments extended method as described in claim 1, it is characterised in that：The ES clusters are
Elasticsearch server clusters.
3. a kind of ElasticSearch fragments extended method as described in claim 1, it is characterised in that：The data acquisition
Terminal is 10,000,000,000 interchangers.
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| CN110427364A (en) * | 2019-06-21 | 2019-11-08 | 北京奇艺世纪科技有限公司 | A kind of data processing method, device, electronic equipment and storage medium |
| CN110716942A (en) * | 2019-10-26 | 2020-01-21 | 南京录信软件技术有限公司 | Large-index rapid splitting method based on Lucene |
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