CN106294380A - The querying method of data base and device - Google Patents

Abstract

The invention provides querying method and the device of a kind of data base, wherein, the method includes: obtain for indicating multiple parameters of the inquiry scene of inquiry data base: carry out integrated decision-making according to multiple parameters, and perform the inquiry to data base according to the query type corresponding with the result of decision.By the present invention, solve problem more single for the inquiry mode of data base in correlation technique, improve the search efficiency of data base.

Description

Database query method and device

technical field

The present invention relates to the communication field, in particular to a database query method and device.

Background technique

For relational database query, the efficiency optimization method in related technologies is to use appropriate index, and use Structured Query Language (Structured Query Language, SQL for short) annotation (such as Oraclehint) to specify the database query optimization method when necessary. For some scenarios, due to uneven data distribution and Hint is not an optimal method, the optimal state of actual efficiency cannot be achieved.

Aiming at the relatively simple query mode of the database in related technologies, no effective solution has been proposed yet.

Contents of the invention

The main purpose of the present invention is to provide a database query method and device to at least solve the problem in the related art that the database query method is relatively simple.

According to one aspect of the present invention, a database query method is provided, including: acquiring multiple parameters used to indicate query scenarios for querying the database; making a comprehensive decision based on the multiple parameters, and according to the query result corresponding to the decision result Type executes a query against the database.

Further, obtaining multiple parameters used to indicate the query scene of querying the database includes: obtaining the first parameter of the ratio of the amount of data returned in the query condition within the first preset statistical time to the total amount of data queried from the database ; Obtain the second parameter of the ratio of the index range of the data to be queried in the database to the index range of all data in the database within the second preset statistical time; obtain the query condition in the third preset statistical time The third parameter for the ratio of database partitions to total partitions.

Further, making a comprehensive decision based on the multiple parameters, and performing a query on the database according to the query type corresponding to the decision result includes: obtaining the first parameter and the preset first threshold and the second threshold respectively. The first comparison result after the comparison, and determine whether to split the database query SQL into a plurality of sub-SQLs according to the first comparison result; after determining whether to split into a plurality of sub-SQLs, obtain the second parameter and the the smaller parameter between the third parameters, and compare the smaller parameter with the preset third threshold and the fourth threshold respectively to obtain a second comparison result, and randomly select according to the second comparison result Specify the index query method to query or the full table scan query method to query.

Further, determining whether to split the database query SQL into multiple sub-SQLs according to the first comparison result includes: splitting into multiple sub-SQLs when the first comparison result is less than or equal to the first threshold; or , when the first comparison result is greater than or equal to the second threshold, do not split into multiple sub-SQLs; or, when the first comparison result is greater than the first threshold and less than the second threshold, randomly Selecting whether to split into multiple sub-SQLs; determining to use a specified index query or a full table scan query according to the second comparison result includes: when the second comparison result is less than or equal to the third threshold, using a specified index query; or , when the second comparison result is greater than or equal to the fourth threshold, use a full table scan query; or, when the second comparison result is greater than the third threshold and less than the fourth threshold, randomly select the specified index queries or the full table scan queries.

Further, after the query of the database is performed according to the comparison result of the specified parameter and a predetermined threshold, the method further includes: saving the plurality of parameters used to indicate querying the database data, and using The current query type takes time to query the database.

Further, after saving the multiple parameters for instructing to query the database data, and using the current query type to query the database, the method further includes: acquiring the locally saved query type Corresponding query time consumption, wherein the query type includes: the full table scan query and the specified index query; compare the time consumption of multiple queries, and adjust the first threshold, the second threshold according to the comparison result The values of the second threshold, the third threshold, and the fourth threshold.

According to another aspect of the present invention, a database query device is provided, including: a first acquisition module, configured to acquire a plurality of parameters used to indicate query scenarios for querying the database; a query module, configured to The parameters are used for comprehensive decision-making, and the query to the database is executed according to the query type corresponding to the decision result.

Further, the first acquisition module includes: a first acquisition unit, configured to acquire the first parameter of the ratio of the amount of data that is limited to be returned in the query condition within the first preset statistical time to the total amount of data queried from the database The second obtaining unit is used to obtain the second parameter of the ratio of the index range of the data to be queried in the database to the index range of all data in the database within the second preset statistical time; the third obtaining unit uses The third parameter is used to obtain the ratio of the database partition to the total partition in the query condition within the third preset statistical time.

Further, the query module includes: a determining unit, configured to obtain a first comparison result after comparing the first parameter with a preset first threshold and a second threshold, and determine according to the first comparison result Whether to split the database query SQL into multiple sub-SQLs; a query unit, after determining whether to split into multiple sub-SQLs, obtain the smaller parameter between the second parameter and the third parameter, and Comparing the smaller parameter with the preset third threshold and fourth threshold respectively to obtain a second comparison result, and randomly selecting a designated index query method for query or a full table scan query method according to the second comparison result Make an inquiry.

Further, the determining unit is further configured to split into multiple sub-SQLs when the first comparison result is less than or equal to the first threshold; or, when the first comparison result is greater than or equal to the second threshold , not split into multiple sub-SQLs; or, when the first comparison result is greater than the first threshold and smaller than the second threshold, randomly select whether to split into multiple sub-SQLs; the query unit also When the second comparison result is less than or equal to the third threshold, use the specified index query; or, when the second comparison result is greater than or equal to the fourth threshold, use a full table scan query; or, in the When the second comparison result is greater than the third threshold and less than the fourth threshold, randomly select the specified index query or the full table scan query.

Through the present invention, a plurality of parameters used to indicate the query scene for querying the database are obtained, and then the multiple parameters are comprehensively decided, and the query to the database is specified according to the query type corresponding to the decision result; it can be seen that in this embodiment By obtaining multiple parameters of the query scene, not just using hints to specify the database for query, through the comprehensive decision of the multiple parameters, it can better adapt to the scene and adopt an optimized query method, which solves the problem of database in related technologies. The query method is relatively simple, which improves the query efficiency of the database.

Description of drawings

The accompanying drawings described here are used to provide a further understanding of the present invention and constitute a part of the application. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations to the present invention. In the attached picture:

Fig. 1 is the flow chart of the query method of the database according to the embodiment of the present invention;

Fig. 2 is a structural block diagram of a query device of a database according to an embodiment of the present invention;

3 is an optional structural block diagram 1 of a query device for a database according to an optional embodiment of the present invention;

Fig. 4 is an optional structural block diagram 2 of a query device of a database according to an optional embodiment of the present invention;

Fig. 5 is a flowchart of a data query algorithm adapted to usage scenarios according to an optional embodiment of the present invention.

detailed description

It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and examples.

The steps shown in the flow diagrams of the figures may be implemented in a computer system, such as a set of computer-executable instructions, and, although a logical order is shown in the flow diagrams, in some cases, may be executed differently from this The steps shown or described are performed in the order shown or described.

The present embodiment provides a method for querying a database. FIG. 1 is a flowchart of a method for querying a database according to an embodiment of the present invention. As shown in FIG. 1 , the steps of the method include:

Step S102: Obtain multiple parameters used to indicate the query scenario for querying the database:

Step S104: Carry out comprehensive decision-making according to multiple parameters, and perform a query on the database according to the query type corresponding to the decision result.

Through the above-mentioned steps S102 and S104 in this embodiment, a plurality of parameters used to indicate the query scene of the query database are obtained, and then the multiple parameters are comprehensively decided, and the query type corresponding to the decision result is specified to the database. Query; it can be seen that in this embodiment, by obtaining multiple parameters of the query scene, not only using hint to specify the database for query, the comprehensive decision of the multiple parameters can better adapt to the scene and adopt optimized query The method solves the problem that the query method of the database is relatively simple in related technologies, and improves the query efficiency of the database.

It should be noted that the multiple parameters involved in this embodiment can be preset to obtain corresponding values, and then can be dynamically adjusted during use.

As for the manner of obtaining multiple parameters used to indicate the query scene of the query database involved in this embodiment, an optional implementation manner of this embodiment may be implemented in the following manner:

Step S11: Obtain the first parameter that limits the ratio of the amount of returned data to the total amount of data queried from the database in the query condition within the first preset statistical time;

Step S12: Obtain the second parameter of the ratio of the index range of data to be queried in the database to the index range of all data in the database within the second preset statistical time;

Step S13: Obtain a third parameter of the ratio of the database partition to the total partition in the query condition within the third preset statistical time.

It can be seen that three different parameters in the query scene can be obtained through the above steps S11 to S13, but these three parameters are only used for illustration and do not constitute a limitation of the present invention; that is, they can be obtained according to actual conditions More parameters. In addition, the first preset statistical time, the second preset statistical time, and the third preset statistical time may or may not be equal in this optional embodiment.

In another optional implementation of this embodiment, the method of performing comprehensive decision-making based on multiple parameters involved in this embodiment and executing a query to the database according to the query type corresponding to the decision result can be implemented in the following manner :

Step S21: Obtain the first comparison result after comparing the first parameter with the preset first threshold and the second threshold respectively, and determine whether to split the database query SQL into multiple sub-SQLs according to the first comparison result;

Step S22: After determining whether to split multiple sub-SQLs, obtain the smaller parameter between the second parameter and the third parameter, and compare the smaller parameter with the preset third threshold and fourth threshold respectively, to obtain The second comparison result, and according to the second comparison result, randomly select a specified index query method to perform query or a full table scan query method to perform query.

Through the above steps S21 and S22, it can be seen that after comparing the first parameter, the second parameter and the third parameter with the predetermined threshold, it is determined whether to split the database, and then it is determined whether to specify the split or unsplit database Index query or full table scan query; this method further refines the factors considered when querying the database, and can make the query more optimized after comprehensively considering multiple parameters of the query scene. As for how to specifically execute the query to the database in the above steps S21 and S22, it can be realized through the following optional methods;

Determining whether to split the database into multiple sub-SQLs based on the first comparison result in the above step S21 can be achieved in the following manner: when the first comparison result is less than or equal to the first threshold, split into multiple sub-SQLs; or, When the first comparison result is greater than or equal to the second threshold, do not split into multiple sub-SQLs; or, when the first comparison result is greater than the first threshold and less than the second threshold, randomly select whether to split into multiple sub-SQLs;

The determination of using the specified index query or the full table scan query based on the second comparison result in the above step S22 can be achieved in the following manner: when the second comparison result is less than or equal to the third threshold, the specified index query is used; or, When the second comparison result is greater than or equal to the fourth threshold, a full table scan query is used; or, when the second comparison result is greater than the third threshold and less than the fourth threshold, a specified index query or a full table scan query is randomly selected.

It can be seen that, in the above steps S21 and S22, an optional method of how to select a query method after comprehensively considering multiple parameters of the query scene is given.

After the above step S22, that is, after executing the query to the database according to the comparison result of the specified parameter and the predetermined threshold, the method of this embodiment may further include: saving a plurality of parameters used to indicate the query database data, and using the current Query type The time spent in querying the database. That is to say, after each query is executed, the parameters used in the query, the predetermined threshold and the time consumption of the query are saved.

For the above-mentioned saved data, after saving multiple parameters for instructing to query database data, and using the current query type to query the time-consuming database, the method of this embodiment may also include:

Obtaining the time-consuming query corresponding to the query type saved locally, where the query type includes: full table scan query and specified index query;

Compare the time consumption of multiple queries, and adjust the values of the first threshold, the second threshold, the third threshold, and the fourth threshold according to the comparison results.

That is to say, by comparing the stored data, the optimal or most suitable query method can be obtained to provide a reliable basis for future queries.

In this embodiment, a database query device is also provided, and the device is used to implement the above embodiments and optional implementation modes, and what has been described will not be repeated. As used below, the terms "module" and "unit" may be a combination of software and/or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.

Fig. 2 is a structural block diagram of a query device of a database according to an embodiment of the present invention. As shown in Fig. 2, the device includes: a first acquisition module 22, which is used to acquire multiple parameters for indicating a query scene of a query database: query module 24. Coupled with the acquisition module 22, it is used to make a comprehensive decision based on multiple parameters, and execute a query to the database according to a query type corresponding to the decision result.

Fig. 3 is an optional structural block diagram 1 of the query device of the database according to an optional embodiment of the present invention. As shown in Fig. 3, the first obtaining module 22 includes: a first obtaining unit 32, which is used to obtain the first preset statistical time The first parameter of the ratio of the amount of data returned in the inner query condition to the total amount of data queried from the database; the second acquisition unit 34 is coupled with the first acquisition unit 32 for obtaining the data within the second preset statistical time The second parameter of the ratio of the index range of the data to be queried in the database to the index range of all data in the database; the third acquisition unit 36 is coupled to the second acquisition unit 34 for obtaining the query within the third preset statistical time The third parameter for the ratio of database partitions to total partitions in the condition.

Fig. 4 is an optional structural block diagram 2 of the query device of the database according to an optional embodiment of the present invention. As shown in Fig. 4, the query module 24 includes: a determination unit 42, which is used to obtain the first parameter and the preset first threshold respectively The first comparison result after comparing with the second threshold, and determine whether to split the database query SQL into multiple sub-SQLs according to the first comparison result; the query unit 44 is coupled with the determination unit 42 for determining whether to split After a plurality of sub-SQLs, obtain the smaller parameter between the second parameter and the third parameter, and compare the smaller parameter with the preset third threshold and the fourth threshold respectively to obtain the second comparison result, and based on the first 2. The comparison result randomly selects the specified index query method for query or the full table scan query method for query.

Optionally, the determining unit 42 is also configured to split into multiple sub-SQLs when the first comparison result is less than or equal to the first threshold; or, when the first comparison result is greater than or equal to the second threshold, not to split into multiple sub-SQLs. sub-SQL; or, when the first comparison result is greater than the first threshold and less than the second threshold, randomly select whether to split into multiple sub-SQLs;

Optionally, the query unit 44 is further configured to use a specified index query when the second comparison result is less than or equal to the third threshold; or, use a full table scan query when the second comparison result is greater than or equal to the fourth threshold; or, When the second comparison result is greater than the third threshold and less than the fourth threshold, a specified index query or a full table scan query is randomly selected.

Optionally, the device involved in this embodiment may also include: after executing the query to the database according to the comparison result of the specified parameter and the predetermined threshold, the device further includes: a saving module, coupled with the query module 22, saving the Indicates multiple parameters for querying database data, and the time spent querying the database with the current query type.

Optionally, after saving a plurality of parameters used to indicate querying database data, and using the current query type to query the database, the device may further include: a second acquiring module, coupled to the saving module, for acquiring The query time corresponding to the query type saved locally, where the query type includes: full table scan query and specified index query;

The comparison module is coupled with the second acquisition module, and is used for comparing the time consumption of multiple queries, and adjusting the values of the first threshold, the second threshold, the third threshold and the fourth threshold according to the comparison results.

The present invention is illustrated below by optional embodiments of the present invention;

This optional embodiment provides a data query algorithm that adapts to usage scenarios. Through this optional embodiment, data query can automatically select an optimized mode as the usage scenarios change.

This optional embodiment adopts parameters according to the type of query, the index range of query, the partition size of the data table of query, the estimation of the data volume of query and the limit of the number of query returns, and selects Structured Query Language (Structured Query Language) after comprehensive evaluation , referred to as SQL) optimization method, the SQL optimization method includes splitting sub-SQL statements according to the partition index, hint selection, etc., and the statistics of the time consumed by each query are used as the basis for the next selection of the optimization method.

The type of query involved in this optional embodiment, the index range of the query, the partition size of the data table for the query, the estimation of the data volume of the query, and the parameters for limiting the number of query returns are described below;

The types of query in this optional embodiment generally include real-time query and statistical query. Real-time query has high time requirements but has a limit on the amount of returned data; statistical query has low time requirements but often requires statistics of all data. Therefore, for these two query types: real-time queries are more inclined to scan by index, and statistical queries are more inclined to full table scans within partitions.

The index range of the query involved in this optional embodiment has a relatively large impact on the selection of the hint. If the index range of the query has reached more than 1/2 of all the data in the index in the partition, and it is necessary to return all the data that meets the conditions, It is suitable for full table scanning; if the index range of the query is less than 1/5 of all the data in this index in the partition, it is suitable for scanning by index. For scenarios where the index range accounts for 1/5 to 1/2 of the entire range, its efficiency is greatly affected by the hardware and software configuration of the database server and storage device, so which method can be used to further use the time consumed by previous queries The statistics are used as the basis for selecting the optimization method next time.

In addition, it should be noted that for scenarios where it is difficult to judge the index range, such as data loss under the time index and location changes under the location index, it is suitable to use the time statistics of historical queries as the basis for the next selection of optimization methods.

In this optional embodiment, for the scenario of splitting sub-SQL, if there is a limit on the number of returned items, then it can be split into sub-SQLs based on the estimated data volume. In specific cases, such as querying data for one month, the number of returned items is limited to 100,000 records, and the estimated 30 million records in one month can be divided into 30 one-day queries, so that only one-day data query can meet the requirements.

For the large amount of data that is queried for one week in this embodiment, it is summarized by location, and the data table is partitioned into one day, which can be split into seven subqueries of one day, so as to avoid the response delay caused by the one-week big data summary.

Fig. 5 is a flow chart of a data query algorithm adapted to a usage scenario according to an optional embodiment of the present invention. As shown in Fig. 5, based on the above description, the data query algorithm of an adaptive usage scenario in this optional embodiment can go through the following steps to realise:

Step S502: Obtain the query type and determine the parameter A, wherein, the parameter A=1 is a real-time query, and A=0 is a report statistics query;

Step S504: Determine the index range of the query, and determine the parameter B, where parameter B=query index range/all data range, if the data table saves 1 month of data, indexes by time, and queries 1 day of data, then B=1/30 ;

Step S506: Determine whether to partition and the size of the partition, and determine the parameter C; wherein, if the data table has no partition, then C=1, if there is a partition and partitioned by time, the partition size is 1 week, and the time range in the query condition is 1 day, then C=1/7;

Step S508: Determine whether the query has a limit on the number of returned items, and estimate the amount of data within the time range in the query condition, and determine the parameter D. For example, the 1-day data volume of the queried data table is estimated to be 1 million, and the number of query returns is limited to 100,000, then D=1/10;

Step S510: According to the parameter D, split the sub-SQL when D<=t1, do not split the sub-SQL when D>=t2, and randomly select whether to split the sub-SQL when t1<D<t2; then according to value=min(B, C ) value to determine whether to use the specified index: value<=k1, specify the index query; value>=k2, the full table scan query; k1<value<k2, randomly use whether to specify the index;

It should be noted that the formula of value=min(B, C) indicates that the smaller value of B and C is taken as the value of value;

Step S512: Save the parameters used in each query, t1, t2, k1, k2 and query time;

Step S514: According to the saved time-consuming data and separate statistics according to the difference of parameter A, determine whether the values of t1, t2, k1, and k2 need to be adjusted.

Through the method of this optional embodiment, for the data statistics of large data tables, it is not necessary to rely on fixed SQL to meet the purpose of efficiency optimization, but to flexibly adopt appropriate optimization methods according to actual usage scenarios, which greatly improves the query while meeting business statistics. efficiency.

The above are only optional embodiments of the present invention, and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. the querying method of a data base, it is characterised in that including:

Acquisition is for indicating multiple parameters of the inquiry scene of inquiry data base:

Carry out integrated decision-making according to the plurality of parameter, and hold according to the query type corresponding with the result of decision The row inquiry to described data base.

Method the most according to claim 1, it is characterised in that obtain the inquiry for indicating inquiry data base Multiple parameters of scene include:

Obtain first preset the data volume limiting return in timing statistics in querying condition with from described data First parameter of the ratio of the data total amount of library inquiry；

Obtain need in described data base in second presets timing statistics inquiry data directory scope with Second parameter of the ratio of the index range of all data in described data base；

Obtain the ratio at the 3rd partitions of database preset in timing statistics in querying condition and total subregion 3rd parameter.

Method the most according to claim 2, it is characterised in that carry out integrated decision-making according to the plurality of parameter, And perform the inquiry of described data base is included according to the query type corresponding with the result of decision:

Obtain after described first parameter compares respectively with default first threshold and Second Threshold One comparative result, and determine whether to split described data base querying SQL according to described first comparative result For many sub-SQL；

After determining whether to be split as many sub-SQL, obtain described second parameter and described 3rd parameter Between less parameter, and described less parameter is entered with the 3rd default threshold value and the 4th threshold value respectively Row compares, and obtains the second comparative result, and randomly chooses assigned indexes according to described second comparative result and look into Inquiry mode carries out inquiring about or full table scan inquiry mode is inquired about.

Method the most according to claim 3, it is characterised in that

Determine whether described data base querying SQL is split as many height according to described first comparative result SQL includes: when described first comparative result is less than or equal to described first threshold, is split as many sub-SQL； Or, when described first comparative result is more than or equal to described Second Threshold, it is not split as many sub-SQL； Or, when described first comparative result is more than described first threshold and is less than described Second Threshold, select at random Select and whether be split as many sub-SQL；

Determine that employing assigned indexes inquiry or full table scan inquiry include according to described second comparative result: When described second comparative result is less than or equal to described three threshold value, use assigned indexes inquiry；Or, institute When stating the second comparative result more than or equal to four threshold values, full table scan is used to inquire about；Or, described second When comparative result is more than described 3rd threshold value and less than described four threshold value, randomly choose described assigned indexes Inquiry or the inquiry of described full table scan.

Method the most according to claim 4, it is characterised in that according to specifying parameter and the ratio of predetermined threshold After relatively result performs the inquiry to described data base, described method also includes:

Preserve described for indicating the plurality of parameter inquiring about described database data, and use current Query type inquire about described data base time-consuming.

Method the most according to claim 5, it is characterised in that be used for indicating the described number of inquiry described in preserving According to the plurality of parameter of database data, and current query type is used to inquire about the time-consuming of described data base Afterwards, described method also includes:

The inquiry corresponding with query type obtaining this locality preservation is time-consuming, and wherein, described query type includes: The inquiry of described full table scan and described assigned indexes are inquired about；

Relatively multiple described inquiries are time-consuming, and according to comparative result adjust described first threshold, described second Threshold value, described 3rd threshold value and the value of described 4th threshold value.

7. the inquiry unit of a data base, it is characterised in that including:

First acquisition module, for obtaining multiple parameters of the inquiry scene for indicating inquiry data base:

Enquiry module, for carrying out integrated decision-making according to the plurality of parameter, and according to the result of decision pair The query type answered performs the inquiry to described data base.

Device the most according to claim 7, it is characterised in that described first acquisition module includes:

First acquiring unit, presets the number limiting return in timing statistics in querying condition for acquisition first The first parameter according to amount with the ratio of the data total amount from described data base querying；

Second acquisition unit, needs inquiry for obtaining in second presets timing statistics in described data base Data directory scope and the second parameter of the ratio of the index range of all data in described data base；

3rd acquiring unit, divides the 3rd data base preset in timing statistics in querying condition for obtaining 3rd parameter of district and the ratio of total subregion.

Device the most according to claim 8, it is characterised in that described enquiry module includes:

Determine unit, enter with default first threshold and Second Threshold respectively for obtaining described first parameter The first comparative result after going relatively, and determine whether described data base according to described first comparative result Query SQL is split as many sub-SQL；

Query unit, for, after determining whether to be split as many sub-SQL, obtaining described second parameter And parameter less between described 3rd parameter, and by described less parameter respectively with the 3rd default threshold Value and the 4th threshold value compare, and obtain the second comparative result, and random according to described second comparative result Select assigned indexes inquiry mode to carry out inquiring about or full table scan inquiry mode is inquired about.

Device the most according to claim 9, it is characterised in that

Described determine unit, be additionally operable to when described first comparative result is less than or equal to described first threshold, It is split as many sub-SQL；Or, when described first comparative result is more than or equal to described Second Threshold, no It is split as many sub-SQL；Or, at described first comparative result more than described first threshold and less than described During Second Threshold, randomly choose and whether be split as many sub-SQL；

Described query unit, is additionally operable to when described second comparative result is less than or equal to described three threshold value, Employing assigned indexes is inquired about；Or, when described second comparative result is more than or equal to four threshold values, use complete Table scan is inquired about；Or, at described second comparative result more than described 3rd threshold value and less than described 4th threshold During value, randomly choose the inquiry of described assigned indexes or the inquiry of described full table scan.