数据库分页语句

本文详细介绍了三种不同的数据库分页实现方法,包括Oracle数据库的三层嵌套查询方式、MySQL的LIMIT关键字使用技巧以及SQL Server中利用ROW_NUMBER()进行分页的具体步骤。这些技术对于提高大型数据集的查询效率至关重要。

Oracle 数据库分页

三层嵌套:

select
        * 
    from
        ( select
            row_.*,
            rownum rownum_ 
        from
            ( select
                this_.id as id63_3_,
                this_.amount as amount63_3_,
                this_.arrival_time as arrival3_63_3_,
                this_.coal_type as coal18_63_3_,
                this_.coal_source as coal15_63_3_,
                this_.diggings as diggings63_3_,
                this_.loadstation as loadsta17_63_3_,
                this_.manufactory as manufac16_63_3_,
                this_.lod_coal_type as lod4_63_3_,
                this_.old_stack_id as old5_63_3_,
                this_.port_sell_id as port6_63_3_,
                this_.remark as remark63_3_,
                this_.source_id as source8_63_3_,
                this_.sourcebz_type as sourcebz9_63_3_,
                this_.stack_id as stack10_63_3_,
                this_.train_no as train11_63_3_,
                this_.trainbusiness_id as trainbu12_63_3_,
                this_.vessel_id as vessel13_63_3_,
                coalclass2_.id as id40_0_,
                coalclass2_.abbr as abbr40_0_,
                coalclass2_.is_activated as is3_40_0_,
                coalclass2_.name as name40_0_,
                coalclass2_.parent_id as parent5_40_0_,
                coalclass2_.parent_name as parent6_40_0_,
                coalclass2_.remark as remark40_0_,
                coalclass2_.type as type40_0_,
                coalclass2_.type_ii as type9_40_0_,
                coalsource3_.id as id41_1_,
                coalsource3_.abbr as abbr41_1_,
                coalsource3_.name as name41_1_,
                coalsource3_.remark as remark41_1_,
                loadstatio4_.id as id48_2_,
                loadstatio4_.abbr as abbr48_2_,
                loadstatio4_.address as address48_2_,
                loadstatio4_.distance as distance48_2_,
                loadstatio4_.is_activated as is5_48_2_,
                loadstatio4_.name as name48_2_,
                loadstatio4_.remark as remark48_2_,
                loadstatio4_.station_code as station8_48_2_ 
            from
                ts_stack_inventory this_,
                bc_coalclass coalclass2_,
                bc_coal_source coalsource3_,
                bc_loadstation loadstatio4_ 
            where
                this_.coal_type=coalclass2_.id(+) 
                and this_.coal_source=coalsource3_.id(+) 
                and this_.loadstation=loadstatio4_.id(+) 
            order by
                this_.id asc ) row_ ) 
        where
            rownum_ <= ? 
            and rownum_ > ?

 

 

MySQL:

 

select
        topic0_.id as id2_,
        topic0_.categoryId as categoryId2_,
        topic0_.createDate as createDate2_,
        topic0_.title as title2_ 
    from
        topic topic0_ 
    where
        not (exists (select
            msg1_.id 
        from
            Msg msg1_ 
        where
            msg1_.topicId=topic0_.id)) limit ?, ?

 

 

SQL Server:

declare @pagesize int,@pageNum int
set @pagesize=10
set @pageNum=2

select * from (
select *,row_number() over(order by 分组字段) rn  
from 表) a
where rn between @pagesize*(@pageNum-1) and @pagesize*(@pageNum)-1

 

基于数据驱动的 Koopman 算子的递归神经网络模型线性化,用于纳米定位系统的预测控制研究(Matlab代码实现)内容概要:本文围绕“基于数据驱动的Koopman算子的递归神经网络模型线性化”展开,旨在研究纳米定位系统的预测控制方法。通过结合数据驱动技术与Koopman算子理论,将非线性系统动态近似为高维线性系统,进而利用递归神经网络(RNN)建模并实现系统行为的精确预测。文中详细阐述了模型构建流程、线性化策略及在预测控制中的集成应用,并提供了完整的Matlab代码实现,便于科研人员复现实验、优化算法并拓展至其他精密控制系统。该方法有效提升了纳米级定位系统的控制精度与动态响应性能。; 适合人群:具备自动控制、机器学习或信号处理背景,熟悉Matlab编程,从事精密仪器控制、智能制造或先进控制算法研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①实现非线性动态系统的数据驱动线性化建模;②提升纳米定位平台的轨迹跟踪与预测控制性能;③为高精度控制系统提供可复现的Koopman-RNN融合解决方案; 阅读建议:建议结合Matlab代码逐段理解算法实现细节,重点关注Koopman观测矩阵构造、RNN训练流程与模型预测控制器(MPC)的集成方式,鼓励在实际硬件平台上验证并调整参数以适应具体应用场景。
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