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    [2021-01-29 10:43:11]  简介:


    php去除nbsp的方法:首先创建一个PHP代码示例文件;然后通过“preg_replace("/(\s|\&nbsp\;| |\xc2\xa0)/", " ", strip_tags($val));”方法去除所有nbsp即可。推荐:《PHP视频教







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  • 10 Common Mistakes Java Developers Make when WritingSQLJava developers mix object-oriented thinking with imperative thinking, depending on their levels of:Skill (anyone can code imperatively)Dogma (s....

    10 Common Mistakes Java Developers Make when Writing SQL

    Java developers mix object-oriented thinking with imperative thinking, depending on their levels of:

    Skill (anyone can code imperatively)Dogma (some use the “Pattern-Pattern”, i.e. the pattern of applying patterns everywhere and giving them names)Mood (true OO is more clumsy to write than imperative code. At first)

    But when Java developers write SQL, everything changes. SQL is a declarative language that has nothing to do with either object-oriented or imperative thinking. It is very easy to express a query in SQL. It is not so easy to express it optimally or correctly. Not only do developers need to re-think their programming paradigm, they also need to think in terms of set theory.

    Here are common mistakes that a Java developer makes when writing SQL through JDBC or jOOQ (in no particular order). For 10 More Common Mistakes, see this article here.

    Here are common mistakes that a Java developer makes when writing SQL (in no particular order):

    1. Forgetting about NULL

    Misunderstanding NULL is probably the biggest mistake a Java developer can make when writing SQL. This is also (but not exclusively) due to the fact that NULL is also called UNKNOWN. If it were only called UNKNOWN, it would be easier to understand. Another reason is that JDBC maps SQL NULL to Java null when fetching data or when binding variables. This may lead to thinking that NULL = NULL (SQL) would behave the same way as null == null (Java)

    One of the crazier examples of misunderstanding NULL is when NULL predicates are used with row value expressions.

    Another, subtle problem appears when misunderstanding the meaning ofNULL in NOT IN anti-joins.

    The Cure:

    Train yourself. There’s nothing but explicitly thinking about NULL, every time you write SQL:

    Is this predicate correct with respect to NULL?Does NULL affect the result of this function?

    2. Processing data in Java memory

    Few Java developers know SQL very well. The occasional JOIN, the odd UNION, fine. But window functions? Grouping sets? A lot of Java developers load SQL data into memory, transform the data into some appropriate collection type, execute nasty maths on that collection with verbose loop structures (at least, before Java 8’s Collection improvements).

    But some SQL databases support advanced (and SQL standard!) OLAP features that tend to perform a lot better and are much easier to write. A (non-standard) example is Oracle’s awesome MODEL clause. Just let the database do the processing and fetch only the results into Java memory. Because after all some very smart guys have optimised these expensive products. So in fact, by moving OLAP to the database, you gain two things:

    Simplicity. It’s probably easier to write correctly in SQL than in JavaPerformance. The database will probably be faster than your algorithm. And more importantly, you don’t have to transmit millions of records over the wire.

    The Cure:

    Every time you implement a data-centric algorithm in Java, ask yourself: Is there a way to let the database perform that work for me?

    3. Using UNION instead of UNION ALL

    It’s a shame that UNION ALL needs an extra keyword compared to UNION. It would be much better if the SQL standard had been defined to support:

    UNION (allowing duplicates)UNION DISTINCT (removing duplicates)

    Not only is the removal of duplicates rarely needed (or sometimes even wrong), it is also quite slow for large result sets with many columns, as the two subselects need to be ordered, and each tuple needs to be compared with its subsequent tuple.

    Note that even if the SQL standard specifies INTERSECT ALL and EXCEPT ALL, hardly any database implements these less useful set operations.

    The Cure:

    Every time you write a UNION, think if you actually wanted to write UNION ALL.

    4. Using JDBC Pagination to paginate large results

    Most databases support some way of paginating ordered results through LIMIT .. OFFSET, TOP .. START AT, OFFSET .. FETCH clauses. In the absence of support for these clauses, there is still the possibility forROWNUM (Oracle) or ROW_NUMBER() OVER() filtering (DB2, SQL Server 2008 and less), which is much faster than pagination in memory. This is specifically true for large offsets!

    The Cure:

    Just use those clauses, or a tool (such as jOOQ) that can simulate those clauses for you.

    5. Joining data in Java memory

    From early days of SQL, some developers still have an uneasy feeling when expressing JOINs in their SQL. There is an inherent fear of JOIN being slow. This can be true if a cost-based optimiser chooses to perform a nested loop, possibly loading complete tables into database memory, before creating a joined table source. But that happens rarely. With appropriate predicates, constraints and indexes, MERGE JOIN and HASH JOIN operations are extremely fast. It’s all about the correct metadata (I cannot cite Tom Kyte often enough for this). Nonetheless, there are probably still quite a few Java developers who will load two tables from separate queries into maps and join them in Java memory in one way or another.

    The Cure:

    If you’re selecting from various tables in various steps, think again to see if you cannot express your query in a single statement.

    6. Using DISTINCT or UNION to remove duplicates from an accidental cartesian product

    With heavy joining, one can loose track of all the relations that are playing a role in a SQL statement. Specifically, if multi-column foreign key relationships are involved, it is possible to forget to add the relevant predicates in JOIN .. ON clauses. This might result in duplicate records, but maybe only in exceptional cases. Some developers may then choose to use DISTINCT to remove those duplicates again. This is wrong in three ways:

    It (may) solve the symptoms but not the problem. It may as well not solve the symptoms in edge-cases.It is slow for large result sets with many columns. DISTINCT performs an ORDER BY operation to remove duplicates.It is slow for large cartesian products, which will still load lots of data into memory

    The Cure:

    As a rule of thumb, when you get unwanted duplicates, always review your JOIN predicates. There’s probably a subtle cartesian product in there somewhere.

    7. Not using the MERGE statement

    This isn’t really a mistake, but probably some lack of knowledge or some fear towards the powerful MERGE statement. Some databases know other forms of UPSERT statements, e.g. MySQL’s ON DUPLICATE KEY UPDATE clause. But MERGE is really so powerful, most importantly in databases that heavily extend the SQL standard, such as SQL Server.

    The Cure:

    If you’re UPSERTING by chaining INSERT and UPDATE or by chaining SELECT .. FOR UPDATE and then INSERT or UPDATE, think again. Apart from risking race conditions, you might be able to express a simpler MERGE statement.

    8. Using aggregate functions instead of window functions

    Before the introduction of window functions, the only means to aggregate data in SQL was by using a GROUP BY clause along with aggregate functions in the projection. This works well in many cases, and if aggregation data needed to be enriched with regular data, the grouped query can be pushed down into a joined subquery.

    But SQL:2003 defined window functions, which are implemented by many popular database vendors. Window functions can aggregate data on result sets that are not grouped. In fact, each window function supports its own, independent PARTITION BY clause, which is an awesome tool for reporting.

    Using window functions will:

    Lead to more readable SQL (less dedicated GROUP BY clauses in subqueries)Improve performance, as a RDBMS is likely to optimise window functions more easily

    The Cure:

    When you write a GROUP BY clause in a subquery, think again if this cannot be done with a window function.

    9. Using in-memory sorting for sort indirections

    The SQL ORDER BY clause supports many types of expressions, including CASE statements, which can be very useful for sort indirections. You should probably never sort data in Java memory because you think that

    SQL sorting is too slowSQL sorting cannot do it

    The Cure:

    If you sort any SQL data in memory, think again if you cannot push sorting into your database. This goes along well with pushing pagination into the database.

    10. Inserting lots of records one by one

    JDBC knows batching, and you should use it. Do not INSERT thousands of records one by one, re-creating a new PreparedStatement every time. If all of your records go to the same table, create a batch INSERT statement with a single SQL statement and multiple bind value sets. Depending on your database and database configuration, you may need to commit after a certain amount of inserted records, in order to keep the UNDO log slim.

    The Cure:

    Always batch-insert large sets of data.

    Some interesting books

    Some very interesting books on similar topics are

    SQL Antipatterns by Bill KarwinSQL Performance Explained by Markus Winand


  • 在VBA使用ADO可以高效的查询数据,但是写SQL查询语句是个有些令人头痛的事情,其实在ADO中用到的SQL语句的语法并不是很复杂,很多时候是由于即要思考SQL的语法,又要用VBA的字符串连接命令,最终搞得一团糟。...



    1. 定义参数


    2. 使用变量


    aPara(2) = VBA.Replace(aPara(2), REPLACE_CHAR, Year(Date))

    3. SQL语句模板

    将SQL模板定义为”SELECT ? FROM ? WHERE ? ? ?”,共有5个问号,对应5个参数。

    4. 可选SQL关键字

    由于GROUP BY和ORDER BY是可选部分,因此如果不需要相关部分的话,请将相应的参数置空,参见“非聚合带排序”。

    5. 动态创建SQL字符串


    sSQL = VBA.Replace(sSQL, REPLACE_CHAR, aPara(i), 1, 1, vbTextCompare)

    6. 完整代码

    Sub CreateSQL()

    Dim sSQL, aPara

    Const REPLACE_CHAR = "?"


    ' aPara = Array("Fields", _ 参数0: 字段

    ' "Table", _ 参数1: 数据表

    ' "Where", _ 参数2: 条件

    ' "Group By", _ 参数3: 分组

    ' "Order By") 参数4: 排序


    ' 聚合SQL

    ' aPara = Array("[班级],[科目],SUM([成绩])", _

    ' "[成绩表$A:K]", _

    ' "[年]='2017'", _

    ' "[班级]", _

    ' "[班级],[科目]")


    ' 非聚合带排序

    aPara = Array("[班级],[科目],[姓名],[成绩]", _

    "[成绩表$A:K]", _

    "[年]='2017'", _

    "", _



    ' 使用变量替换参数

    aPara(2) = VBA.Replace(aPara(2), REPLACE_CHAR, Year(Date))


    sSQL = "SELECT ? FROM ? WHERE ? ? ?"

    For i = 0 To 4

    If i > 2 And Len(aPara(i)) > 0 Then

    aPara(i) = IIf(i = 3, "GROUP BY ", "ORDER BY ") & aPara(i)

    End If

    sSQL = VBA.Replace(sSQL, REPLACE_CHAR, aPara(i), 1, 1, vbTextCompare)

    'Debug.Print sSQL


    Debug.Print sSQL

    End Sub

    7. SQL查询字符串

    ' 聚合SQL

    SELECT [班级],[科目],SUM([成绩]) FROM [成绩表$A:K] WHERE [年]='2017' GROUP BY [班级] ORDER BY [班级],[科目]

    ' 非聚合带排序

    SELECT [班级],[科目],[姓名],[成绩] FROM [成绩表$A:K] WHERE [年]='2018' ORDER BY [班级],[科目]


  • 数据库字段不能为中文,否则java里面写SQL写不出来  select * from 岁末合约_结果; 解决办法==》用as将中文列名 as成对应实体类中的属性名 select user_id as userid, bill_id as billid, 客户姓名 as cusname ,...
    <span style="font-size:14px;">    select * from 岁末合约_结果;

    解决办法==》用as将中文列名 as成对应实体类中的属性名
    <pre name="code" class="sql"><span style="font-size:14px;">select user_id as userid, bill_id as billid, 客户姓名 as cusname , 外呼时间 as outcalltime,
          业务名称 as ywname, 外呼人员 as outcallman, 数据来源 as datasource, 营销成功项目 as yxsucesspro,
          预约时间 as yytime, 余额 as leftmoney, 办理合约名称 as blhyname, 办理时间 as bltime, 办理操作人 as blman,
          办理组织 as blorg, 撤销合约名称 as cxhyname, 撤销时间 as cxtime, 撤销操作人 as cxman, 撤销组织 as cxorg, 
          终止合约名称 as zzhyname, 终止时间 as zzhytime, 终止操作人 as zzhyman, 终止组织 as zzhyorg,批量调整金额 as pltzmoney,
          pos券充值金额 as posczmoney, 新增是否冲突 as isaddct, 更新时间 as updatetime 
          from 岁末合约_结果  a</span>


  • 用spark实现查数据库对象的方法,话不多说直接撸代码: SparkSession spark = ... .appName("JavaWordCount").master("local") .getOrCreate(); //前提map里面已经有相应的参数了 String url = map.get("...
  • 发现csdn上的连接池都是配设xml的,就手写了一份数据库连接池(java),连接sqlserver,里面一共两个java代码,Conn类包含了Connection和标志位,myconnection包含了数据库连接池的使用:获取连接,增加连接,释放...
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    2020-02-08 23:30:31
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  • javaSQL查询语句有like '%?%'怎么

    万次阅读 多人点赞 2018-04-10 22:50:03
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  • 某天,在群里看见有个人 问 sqlService里面有2000万条数据 需要转储到orcale中。什么方式比较好,后来一琢磨非多线程莫属啊~;我这里没有那么多数据,所以我就模拟了下 一次存入10万条数据,看有多快~;上代码。在...
  • 【实例简介】这是本人花了半个月出来的一个基于java编程和SqlServer数据库技术结合的Swing项目,是一个超市管理系统,里面包含着超市管理的基本业务流程,(员工管理,部门管理,商品管理,销售管理,)还包含数据库...
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  • 这个是MyEclipse连接SQL Server JAVA源代码代码,里面都是好的方法,直接可以调用
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  • Java sql查询

    千次阅读 2017-11-09 14:36:28
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  •  某天,在群里看见有个人 问 sqlService里面有2000万条数据 需要转储到orcale中。什么方式比较好,后来一琢磨非多线程莫属啊~; 我这里没有那么多数据,所以我就模拟了下 一次存入10万条数据,看有多快~;上代码。...
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  • 1,新建java项目(或者web项目,这里以java为例),以user表为例子 ...3,这里我将数据库的连接代码封装在DBConnectionUtil.java里面 package com.beiruan.util; import java.io.IOException; imp



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