Multidimensional data model access method and device

Abstract

The invention provides a multidimensional data model access method and a multidimensional data model access device. The method comprises the following steps of: receiving and analyzing a statement inputted by a user; converting a query object and query object filtering conditions of the statement into a multidimensional data model query object which can be received by a query engine; and querying a data warehouse according to the multidimensional data model query object, and then generating a query result object. The method and device disclosed by the invention have a syntax error prompt function, thereby facilitating the changes and writing of statements implemented by servicers; the servicers can verify whether an error data model in the data warehouse is configured correctly according to query results; and the accessing of the users to multidimensional data is facilitated.

Description

technical field

[0001] The invention relates to data query technology, in particular to a multi-dimensional data model access method and device. Background technique

[0002] In the prior art, for accessing multidimensional data, data is usually queried by handwriting. Since data is mostly stored in star schema and snowflake schema, the efficiency of querying data is very low and lacks business meaning, which is not conducive to understanding data from the perspective of multidimensional data model.

[0003] For example, when querying data tables in the database through SQL statements, for ROLAP (Relational On-Line Analytical Processing), the data is queried mainly by writing SQL statements. The disadvantages of querying the multidimensional data model through SQL are: SQL writing is difficult, debugging is difficult, and a multidimensional query needs to write a long SQL, which is very difficult to write manually. It requires business personnel to have a thorough understan...

Examples

Embodiment 1

[0042] Such as figure 1 As shown, this embodiment provides a multidimensional data model access method, the method comprising:

[0043] Step S101: Receive a sentence input by a user, and analyze the sentence.

[0044] In step S101, analyzing the sentence includes: a lexical analysis step and a grammar analysis step. When the statement contains lexical syntax, prompt the cause of the grammatical error and the location of the grammatical error; when the statement contains a grammatical error, the location of the query content, query object and filter condition is wrong, and the three Check the semantic level of the mismatch between them, and prompt the cause and location of the semantic error.

[0045] Step S102: Transform the query object and query object filtering conditions of the statement into a multi-dimensional data model query object that can be received by the data query engine. The query object of the statement includes information such as dimensions, measures, and ...

Embodiment 2

[0077] Such as Figure 8 As shown, this embodiment provides a multi-dimensional data model access device, the multi-dimensional data model access device includes: a statement parsing unit 801 , a query object construction unit 802 and a data query unit 803 .

[0078] The sentence parsing unit 801 is configured to receive a sentence input by a user, and analyze the sentence. The sentence parsing unit includes: a lexical parsing module 804 and a grammar parsing module 805 .

[0079] When described sentence comprises lexical, lexical analysis module 804 prompts to the reason of lexical error and the position of lexical error, as whether the writing of dimension, measure complies with the rule; When described sentence comprises grammatical error, grammatical analysis module 805 Check the wrong location of the query content, query object and filter conditions, and the mismatch between the three at the semantic level, and prompt the cause and location of the semantic error.

[008...

technical field

[0001] The invention relates to data query technology, in particular to a multi-dimensional data model access method and device. Background technique

[0002] In the prior art, for accessing multidimensional data, data is usually queried by handwriting. Since data is mostly stored in star schema and snowflake schema, the efficiency of querying data is very low and lacks business meaning, which is not conducive to understanding data from the perspective of multidimensional data model.

[0003] For example, when querying data tables in the database through SQL statements, for ROLAP (Relational On-Line Analytical Processing), the data is queried mainly by writing SQL statements. The disadvantages of querying the multidimensional data model through SQL are: SQL writing is difficult, debugging is difficult, and a multidimensional query needs to write a long SQL, which is very difficult to write manually. It requires business personnel to have a thorough understan...

Examples

Embodiment 1

[0042] Such as figure 1 As shown, this embodiment provides a multidimensional data model access method, the method comprising:

[0043] Step S101: Receive a sentence input by a user, and analyze the sentence.

[0044] In step S101, analyzing the sentence includes: a lexical analysis step and a grammar analysis step. When the statement contains lexical syntax, prompt the cause of the grammatical error and the location of the grammatical error; when the statement contains a grammatical error, the location of the query content, query object and filter condition is wrong, and the three Check the semantic level of the mismatch between them, and prompt the cause and location of the semantic error.

[0045] Step S102: Transform the query object and query object filtering conditions of the statement into a multi-dimensional data model query object that can be received by the data query engine. The query object of the statement includes information such as dimensions, measures, and ...

Embodiment 2

[0077] Such as Figure 8 As shown, this embodiment provides a multi-dimensional data model access device, the multi-dimensional data model access device includes: a statement parsing unit 801 , a query object construction unit 802 and a data query unit 803 .

[0078] The sentence parsing unit 801 is configured to receive a sentence input by a user, and analyze the sentence. The sentence parsing unit includes: a lexical parsing module 804 and a grammar parsing module 805 .

[0079] When described sentence comprises lexical, lexical analysis module 804 prompts to the reason of lexical error and the position of lexical error, as whether the writing of dimension, measure complies with the rule; When described sentence comprises grammatical error, grammatical analysis module 805 Check the wrong location of the query content, query object and filter conditions, and the mismatch between the three at the semantic level, and prompt the cause and location of the semantic error.

[008...

Images