CN110716954A - Elasticissearch data query method and system - Google Patents

Elasticissearch data query method and system Download PDF

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Publication number
CN110716954A
CN110716954A CN201910982405.2A CN201910982405A CN110716954A CN 110716954 A CN110716954 A CN 110716954A CN 201910982405 A CN201910982405 A CN 201910982405A CN 110716954 A CN110716954 A CN 110716954A
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CN
China
Prior art keywords
source code
sql
editing
plug
elasticsearch
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Pending
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CN201910982405.2A
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Chinese (zh)
Inventor
王帝
王光武
饶鑫淞
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Beijing Sohu New Media Information Technology Co Ltd
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Beijing Sohu New Media Information Technology Co Ltd
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Priority to CN201910982405.2A priority Critical patent/CN110716954A/en
Publication of CN110716954A publication Critical patent/CN110716954A/en
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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
    • G06F16/242—Query formulation
    • G06F16/2433—Query languages
    • G06F16/2445—Data retrieval commands; View definitions
    • 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
    • G06F16/242—Query formulation
    • 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

Abstract

The invention discloses an Elasticissearch data query method and system, wherein the method comprises the following steps: and acquiring the source code of the Elasticisearch-SQL plug-in on a code open source website, and editing the source code of the Elasticisearch-SQL plug-in so that the edited source code supports more SQL query functions. According to the invention, by further editing the source code of the Elasticissearch-SQL plug-in, Elasticissearch data query can be more perfectly carried out through SQL, and the user experience is improved.

Description

Elasticissearch data query method and system
Technical Field
The invention relates to the technical field of data processing, in particular to an Elasticissearch data query method and system.
Background
In today's big data age, it is often necessary to perform a wide variety of complex queries on data, such as aggregation, ordering, grouping, filtering, etc. queries. At present, programmers basically use SQL (Structured Query Language) to perform data Query, but the Elasticsearch itself does not support the Query mode of SQL, and an SQL plug-in needs to be additionally developed. At present, the functions supported by the existing Elasticissearch-SQL plug-in are somewhat simple and are not perfect.
Therefore, how to effectively perform the Elasticsearch data query through the SQL is a problem to be solved.
Disclosure of Invention
In view of this, the invention provides an Elasticsearch data query method, which can perform Elasticsearch data query more perfectly through SQL.
The invention provides an Elasticissearch data query method, which comprises the following steps:
acquiring a source code of an Elasticissearch-SQL plug-in on a code open source website;
and editing the source code of the Elasticissearch-SQL plug-in so that the edited source code supports more SQL query functions.
Preferably, the editing the source code of the Elasticsearch-SQL plug-in, so that the edited source code supports more SQL query functions, includes:
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement can be used in an order by clause;
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement supports in and not in judgment;
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement to be used in a where clause;
editing the source code of the Elasticsearch-SQL plug-in to enable computation in the case where clause.
Preferably, the editing the source code of the Elasticsearch-SQL plug-in to make the edited source code support more SQL query functions further includes:
editing the source code of the Elasticsearch-SQL plug-in to enable the user to specify the size of each bucket of the aggregation by restriction;
the source code of the Elasticsearch-SQL plug-in is edited to enable the user to specify the size of the aggregated partition by restriction.
Preferably, the editing the source code of the Elasticsearch-SQL plug-in to make the edited source code support more SQL query functions further includes:
editing the source code of the Elasticsearch-SQL plug-in to enable the use of if functions.
Preferably, the editing the source code of the Elasticsearch-SQL plug-in to make the edited source code support more SQL query functions further includes:
editing the source code of the Elasticissearch-SQL plug-in so that the round () function can specify the preset number of bits after the decimal point is reserved.
An Elasticissearch data query system, comprising:
the acquisition module is used for acquiring a source code of the Elasticissearch-SQL plug-in on a code open source website;
and the editing module is used for editing the source code of the Elasticissearch-SQL plug-in so that the edited source code supports more SQL query functions.
Preferably, the editing module is specifically configured to, when the source code of the Elasticsearch-SQL plug-in is edited to make the edited source code support more SQL query functions:
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement can be used in an order by clause;
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement supports in and not in judgment;
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement to be used in a where clause;
editing the source code of the Elasticsearch-SQL plug-in to enable computation in the case where clause.
Preferably, when the editing module edits the source code of the Elasticsearch-SQL plug-in to make the edited source code support more SQL query functions, the editing module is further specifically configured to:
editing the source code of the Elasticsearch-SQL plug-in to enable the user to specify the size of each bucket of the aggregation by restriction;
the source code of the Elasticsearch-SQL plug-in is edited to enable the user to specify the size of the aggregated partition by restriction.
Preferably, when the editing module edits the source code of the Elasticsearch-SQL plug-in to make the edited source code support more SQL query functions, the editing module is further specifically configured to:
editing the source code of the Elasticsearch-SQL plug-in to enable the use of if functions.
Preferably, when the editing module edits the source code of the Elasticsearch-SQL plug-in to make the edited source code support more SQL query functions, the editing module is further specifically configured to:
editing the source code of the Elasticissearch-SQL plug-in so that the round () function can specify the preset number of bits after the decimal point is reserved.
In summary, the invention discloses an elastic search data query method, when the elastic search data query needs to be realized, a source code of an elastic search-SQL plug-in is first acquired on a code open source website, and then the source code of the elastic search-SQL plug-in is edited, so that the edited source code supports more SQL query functions. According to the invention, by further editing the source code of the Elasticissearch-SQL plug-in, Elasticissearch data query can be more perfectly carried out through SQL, and the user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method in embodiment 1 of an Elasticsearch data query method disclosed in the present invention;
FIG. 2 is a flowchart of a method of embodiment 2 of the method for querying Elasticissearch data disclosed in the present invention;
FIG. 3 is a schematic structural diagram of an embodiment 1 of an Elasticissearch data query system disclosed in the present invention;
fig. 4 is a schematic structural diagram of an embodiment 2 of an Elasticsearch data query system disclosed in the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, which is a flowchart of a method in embodiment 1 of the method for querying Elasticsearch data disclosed in the present invention, the method may include the following steps:
s101, acquiring a source code of an Elasticissearch-SQL plug-in on a code open source website;
when the Elasticissearch data query needs to be realized, firstly, acquiring a source code of an Elasticissearch-SQL plug-in existing in the same industry on an open source website; for example, the source code of an elastic search-SQL plug-in which the same industry already has is obtained on a github code open source website.
S102, editing the source code of the elastic search-SQL plug-in so that the edited source code supports more SQL query functions.
After the source code of the existing Elasticissearch-SQL plug-in the same industry is obtained, the obtained source code of the Elasticissearch-SQL plug-in is further analyzed, and the obtained source code of the Elasticissearch-SQL plug-in is edited according to the analysis result, so that the edited source code of the Elasticissearch-SQL plug-in can support more SQL query functions compared with the source code of the existing Elasticissearch-SQL plug-in the same industry.
In summary, in the above embodiment, when the Elasticsearch data query needs to be implemented, first the source code of the Elasticsearch-SQL plug-in is obtained on the code open source website, and then the source code of the Elasticsearch-SQL plug-in is edited, so that the edited source code supports more SQL query functions. According to the invention, by further editing the source code of the Elasticissearch-SQL plug-in, Elasticissearch data query can be more perfectly carried out through SQL, and the user experience is improved.
As shown in fig. 2, which is a flowchart of a method of embodiment 2 of the method for querying Elasticsearch data disclosed in the present invention, the method may include the following steps:
s201, acquiring a source code of an Elasticissearch-SQL plug-in on a code open source website;
when the Elasticissearch data query needs to be realized, firstly, acquiring a source code of an Elasticissearch-SQL plug-in existing in the same industry on an open source website; for example, the source code of an elastic search-SQL plug-in which the same industry already has is obtained on a github code open source website.
S202, editing a source code of the elastic search-SQL plug-in so as to enable a case where statement can be used in an order by clause;
s203, editing a source code of the elastic search-SQL plug-in to enable a case where statement supports in and not in judgment;
s204, editing the source code of the elastic search-SQL plug-in so as to enable a case where statement to be used in a where clause;
s205, editing a source code of the elastic search-SQL plug-in so as to enable calculation to be carried out in a case where clause;
s206, editing the source code of the Elasticissearch-SQL plug-in so that the user can specify the size of each aggregated bucket through limitation;
s207, editing the source code of the elastic search-SQL plug-in so that the user can specify the size of the aggregated partition by limitation;
s208, editing the source code of the elastic search-SQL plug-in so as to use the if function;
s209, editing the source code of the Elasticissearch-SQL plug-in so that the round () function can specify the preset digit after the decimal point is reserved.
After the source code of the existing Elasticissearch-SQL plug-in the same industry is obtained, the obtained source code of the Elasticissearch-SQL plug-in is further analyzed, and the obtained source code of the Elasticissearch-SQL plug-in is edited according to the analysis result, so that the edited source code of the Elasticissearch-SQL plug-in can support more SQL query functions compared with the source code of the existing Elasticissearch-SQL plug-in the same industry.
Specifically, the source code of the acquired existing elastic search-SQL plug-in the same industry can be further edited, so that the edited source code of the elastic search-SQL plug-in can enable a case where statement can be used in an order by clause, and enable the case where statement to support in and not in judgment, and enable the case where statement can be used in a where clause, and enable calculation to be performed in the case where statement can be used, for example, case where 1 ═ 1then field _1+ field _2else 0end is just that field _1+ field _2 can be calculated, and the source code of the existing elastic search-SQL plug-in is not available, but only can be a field value, and cannot be calculated; the source code of the edited Elasticsearch-SQL plug-in can enable a user to specify the size of each bucket through limit, and enable the user to specify the aggregated shardsize through limit; the source code of the edited Elasticsearch-SQL plug-in can also be enabled to use if functions, such as: a select if (sex ═ 1', ' male ', ' female ') from t _ user; the source code of the edited Elasticsearch-SQL plug-in can enable the round () function to specify the preset number of bits after the decimal point is reserved.
In summary, the invention can expand the SQL semantic analysis and support more flexible calculation by analyzing the acquired source code of the existing Elasticsearch-SQL plug-in and editing the source code of the existing Elasticsearch-SQL plug-in according to the analysis result, so that the edited source code of the Elasticsearch-SQL plug-in can support more SQL query functions, and the data query experience of the user is improved.
As shown in fig. 3, which is a schematic structural diagram of an embodiment 1 of an Elasticsearch data query system disclosed in the present invention, the system may include:
an obtaining module 301, configured to obtain a source code of an Elasticsearch-SQL plug-in on a code open source website;
when the Elasticissearch data query needs to be realized, firstly, acquiring a source code of an Elasticissearch-SQL plug-in existing in the same industry on an open source website; for example, the source code of an elastic search-SQL plug-in which the same industry already has is obtained on a github code open source website.
The editing module 302 is configured to edit the source code of the Elasticsearch-SQL plug-in, so that the edited source code supports more SQL query functions.
After the source code of the existing Elasticissearch-SQL plug-in the same industry is obtained, the obtained source code of the Elasticissearch-SQL plug-in is further analyzed, and the obtained source code of the Elasticissearch-SQL plug-in is edited according to the analysis result, so that the edited source code of the Elasticissearch-SQL plug-in can support more SQL query functions compared with the source code of the existing Elasticissearch-SQL plug-in the same industry.
In summary, in the above embodiment, when the Elasticsearch data query needs to be implemented, first the source code of the Elasticsearch-SQL plug-in is obtained on the code open source website, and then the source code of the Elasticsearch-SQL plug-in is edited, so that the edited source code supports more SQL query functions. According to the invention, by further editing the source code of the Elasticissearch-SQL plug-in, Elasticissearch data query can be more perfectly carried out through SQL, and the user experience is improved.
As shown in fig. 4, which is a schematic structural diagram of an embodiment 2 of an Elasticsearch data query system disclosed in the present invention, the system may include:
the obtaining module 401 is configured to obtain a source code of an Elasticsearch-SQL plug-in on a code open source website;
when the Elasticissearch data query needs to be realized, firstly, acquiring a source code of an Elasticissearch-SQL plug-in existing in the same industry on an open source website; for example, the source code of an elastic search-SQL plug-in which the same industry already has is obtained on a github code open source website.
An editing module 402, configured to edit a source code of the Elasticsearch-SQL plug-in, so that a case where statement can be used in the order by clause;
the editing module 402 is further configured to edit a source code of the Elasticsearch-SQL plug-in, so that a case where statement supports in and not in judgment;
the editing module 402 is further configured to edit the source code of the Elasticsearch-SQL plug-in, so that a case where statement can be used in a where clause;
the editing module 402 is further configured to edit the source code of the Elasticsearch-SQL plug-in, so that a calculation can be performed in the casewhere clause;
an editing module 402, configured to edit the source code of the Elasticsearch-SQL plug-in, so that the user can specify the size of each aggregated bucket by restriction;
an editing module 402, configured to edit the source code of the Elasticsearch-SQL plug-in, so that the user can specify the size of the aggregated partition by restriction;
an editing module 402, configured to edit the source code of the Elasticsearch-SQL plug-in to enable use of the if function;
the editing module 402 is further configured to edit the source code of the Elasticsearch-SQL plug-in, so that the round () function can specify a preset number of bits after being reserved to the decimal point.
After the source code of the existing Elasticissearch-SQL plug-in the same industry is obtained, the obtained source code of the Elasticissearch-SQL plug-in is further analyzed, and the obtained source code of the Elasticissearch-SQL plug-in is edited according to the analysis result, so that the edited source code of the Elasticissearch-SQL plug-in can support more SQL query functions compared with the source code of the existing Elasticissearch-SQL plug-in the same industry.
Specifically, the source code of the acquired existing elastic search-SQL plug-in the same industry can be further edited, so that the edited source code of the elastic search-SQL plug-in can enable a case where statement can be used in an order by clause, and enable the case where statement to support in and not in judgment, and enable the case where statement can be used in a where clause, and enable calculation to be performed in the case where statement can be used, for example, case where 1 ═ 1then field _1+ field _2else 0end is just that field _1+ field _2 can be calculated, and the source code of the existing elastic search-SQL plug-in is not available, but only can be a field value, and cannot be calculated; the source code of the edited Elasticsearch-SQL plug-in can enable a user to specify the size of each bucket through limit, and enable the user to specify the aggregated shardsize through limit; the source code of the edited Elasticsearch-SQL plug-in can also be enabled to use if functions, such as: a select if (sex ═ 1', ' male ', ' female ') from t _ user; the source code of the edited Elasticsearch-SQL plug-in can enable the round () function to specify the preset number of bits after the decimal point is reserved.
In summary, the invention can expand the SQL semantic analysis and support more flexible calculation by analyzing the acquired source code of the existing Elasticsearch-SQL plug-in and editing the source code of the existing Elasticsearch-SQL plug-in according to the analysis result, so that the edited source code of the Elasticsearch-SQL plug-in can support more SQL query functions, and the data query experience of the user is improved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. An Elasticissearch data query method is characterized by comprising the following steps:
acquiring a source code of an Elasticissearch-SQL plug-in on a code open source website;
and editing the source code of the Elasticissearch-SQL plug-in so that the edited source code supports more SQL query functions.
2. The method of claim 1, wherein editing the source code of the Elasticsearch-SQL plug-in such that the edited source code supports more SQL query functions comprises:
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement can be used in an order by clause;
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement supports in and not in judgment;
editing the source code of the Elasticissearch-SQL plug-in so as to enable casewhere sentences to be used;
editing the source code of the Elasticsearch-SQL plug-in to enable computation in the case where clause.
3. The method of claim 2, wherein editing the source code of the Elasticsearch-SQL plug-in such that the edited source code supports more SQL query functions further comprises:
editing the source code of the Elasticsearch-SQL plug-in to enable the user to specify the size of each bucket of the aggregation by restriction;
the source code of the Elasticsearch-SQL plug-in is edited to enable the user to specify the size of the aggregated partition by restriction.
4. The method of claim 3, wherein editing the source code of the Elasticsearch-SQL plug-in such that the edited source code supports more SQL query functions further comprises:
editing the source code of the Elasticsearch-SQL plug-in to enable the use of if functions.
5. The method of claim 4, wherein editing the source code of the Elasticsearch-SQL plug-in such that the edited source code supports more SQL query functions further comprises:
editing the source code of the Elasticissearch-SQL plug-in so that the round () function can specify the preset number of bits after the decimal point is reserved.
6. An Elasticsearch data query system, comprising:
the acquisition module is used for acquiring a source code of the Elasticissearch-SQL plug-in on a code open source website;
and the editing module is used for editing the source code of the Elasticissearch-SQL plug-in so that the edited source code supports more SQL query functions.
7. The system according to claim 6, wherein the editing module, when executing editing of the source code of the Elasticsearch-SQL plug-in, is specifically configured to:
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement can be used in an order by clause;
editing the source code of the Elasticissearch-SQL plug-in so as to enable a case where statement supports in and not in judgment;
editing the source code of the Elasticissearch-SQL plug-in so as to enable casewhere sentences to be used;
editing the source code of the Elasticsearch-SQL plug-in to enable computation in the case where clause.
8. The system according to claim 7, wherein the editing module, when executing editing of the source code of the Elasticsearch-SQL plug-in, is further configured to, when the edited source code supports more SQL query functions:
editing the source code of the Elasticsearch-SQL plug-in to enable the user to specify the size of each bucket of the aggregation by restriction;
the source code of the Elasticsearch-SQL plug-in is edited to enable the user to specify the size of the aggregated partition by restriction.
9. The system according to claim 8, wherein the editing module, when executing editing of the source code of the Elasticsearch-SQL plug-in, is further configured to, when the edited source code supports more SQL query functions:
editing the source code of the Elasticsearch-SQL plug-in to enable the use of if functions.
10. The system according to claim 9, wherein the editing module, when executing editing the source code of the Elasticsearch-SQL plug-in, is further configured to, when the edited source code supports more SQL query functions:
editing the source code of the Elasticissearch-SQL plug-in so that the round () function can specify the preset number of bits after the decimal point is reserved.
CN201910982405.2A 2019-10-15 2019-10-15 Elasticissearch data query method and system Pending CN110716954A (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160203548A1 (en) * 2007-02-09 2016-07-14 Xcira, Inc. Integrated auctioning environment platform
CN106934062A (en) * 2017-03-28 2017-07-07 广东工业大学 A kind of realization method and system of inquiry elasticsearch
CN107153535A (en) * 2017-03-27 2017-09-12 武汉斗鱼网络科技有限公司 A kind of operation ElasticSearch method and device
CN109145009A (en) * 2018-08-19 2019-01-04 杭州安恒信息技术股份有限公司 A method of ElasticSearch is retrieved based on SQL

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160203548A1 (en) * 2007-02-09 2016-07-14 Xcira, Inc. Integrated auctioning environment platform
CN107153535A (en) * 2017-03-27 2017-09-12 武汉斗鱼网络科技有限公司 A kind of operation ElasticSearch method and device
CN106934062A (en) * 2017-03-28 2017-07-07 广东工业大学 A kind of realization method and system of inquiry elasticsearch
CN109145009A (en) * 2018-08-19 2019-01-04 杭州安恒信息技术股份有限公司 A method of ElasticSearch is retrieved based on SQL

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
SHI-YUAN: "《Update README.md•NLPchina/elasticsearch-sql》", 《HTTPS://GITHUB.COM/NLPCHINA/ELASTICSEARCH-SQL》 *
郑新宇: "基于Elasticsearch的实时搜索系统的设计与实现", 《中国优秀硕士学位论文全文数据库(信息科技辑)》 *

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Application publication date: 20200121