1.项目引入mysql和oracle驱动

2.将mysql和oracle驱动上传到hdfs

3.远程调试源代码如下：

import org.apache.spark.sql.SQLContext

import org.apache.spark.{SparkConf, SparkContext}

object jdbc {

def main(args: Array[String]): Unit = {

System.setProperty("hadoop.home.dir", "D:\\hadoop") //加载hadoop组件

val conf = new SparkConf().setAppName("mysql").setMaster("spark://192.168.66.66:7077")

.set("spark.executor.memory", "1g")

.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")

//.setJars(Seq("D:\\workspace\\scala\\out\\scala.jar"))//加载远程spark

.setJars(Array("hdfs://192.168.66.66:9000/spark-jars/ojdbc14-10.2.0.1.0.jar",

"hdfs://192.168.66.66:9000/spark-jars/mysql-connector-java-5.1.39.jar"))

val sc = new SparkContext(conf)

val sqlContext = new SQLContext(sc)

//操作MySQL

val mysql = sqlContext.read.format("jdbc").option("url","jdbc:mysql://192.168.66.66:3306/test").

option("dbtable","student").option("driver","com.mysql.jdbc.Driver").

option("user","root").option("password","1").load()

mysql.show()

val mysql2= sqlContext.read.format("jdbc").options(

Map(

"driver" -> "com.mysql.jdbc.Driver",

"url" -> "jdbc:mysql://192.168.66.66:3306",

"dbtable" -> "test.student",

"user" -> "root",

"password" -> "1",

"fetchsize" -> "3")).load()

mysql2.show

mysql.registerTempTable("student")

mysql.sqlContext.sql("select * from student").collect().foreach(println)

//操作ORACLE

val oracle= sqlContext.read.format("jdbc").options(

Map(

"driver" -> "oracle.jdbc.driver.OracleDriver",

"url" -> "jdbc:oracle:thin:@10.2.1.169:1521:BIT",

"dbtable" -> "tab_lg",

"user" -> "lxb",

"password" -> "lxb123",

"fetchsize" -> "3")).load()

//oracle.show

oracle.registerTempTable("tab_lg")

oracle.sqlContext.sql("select * from tab_lg limit 10").collect().foreach(println)

}

}

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties

SLF4J: Class path contains multiple SLF4J bindings.

SLF4J: Found binding in [jar:file:/C:/Users/xinfang/.m2/repository/org/slf4j/slf4j-log4j12/1.7.22/slf4j-log4j12-1.7.22.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: Found binding in [jar:file:/C:/Users/xinfang/.m2/repository/org/apache/logging/log4j/log4j-slf4j-impl/2.4.1/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.

SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]

17/12/11 16:03:49 INFO SparkContext: Running Spark version 1.6.3

17/12/11 16:03:51 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

17/12/11 16:03:51 INFO SecurityManager: Changing view acls to: xinfang

17/12/11 16:03:51 INFO SecurityManager: Changing modify acls to: xinfang

17/12/11 16:03:51 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(xinfang); users with modify permissions: Set(xinfang)

17/12/11 16:03:52 INFO Utils: Successfully started service 'sparkDriver' on port 55112.

17/12/11 16:03:53 INFO Slf4jLogger: Slf4jLogger started

17/12/11 16:03:53 INFO Remoting: Starting remoting

17/12/11 16:03:53 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@172.20.107.151:55125]

17/12/11 16:03:53 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 55125.

17/12/11 16:03:53 INFO SparkEnv: Registering MapOutputTracker

17/12/11 16:03:53 INFO SparkEnv: Registering BlockManagerMaster

17/12/11 16:03:53 INFO DiskBlockManager: Created local directory at C:\Users\xinfang\AppData\Local\Temp\blockmgr-7ffc898d-c1fc-42e3-bcd6-72c47e1564cd

17/12/11 16:03:53 INFO MemoryStore: MemoryStore started with capacity 1122.0 MB

17/12/11 16:03:54 INFO SparkEnv: Registering OutputCommitCoordinator

17/12/11 16:03:54 INFO Utils: Successfully started service 'SparkUI' on port 4040.

17/12/11 16:03:54 INFO SparkUI: Started SparkUI at http://172.20.107.151:4040

17/12/11 16:03:54 INFO SparkContext: Added JAR hdfs://192.168.66.66:9000/spark-jars/ojdbc14-10.2.0.1.0.jar at hdfs://192.168.66.66:9000/spark-jars/ojdbc14-10.2.0.1.0.jar with timestamp 1512979434526

17/12/11 16:03:54 INFO SparkContext: Added JAR hdfs://192.168.66.66:9000/spark-jars/mysql-connector-java-5.1.39.jar at hdfs://192.168.66.66:9000/spark-jars/mysql-connector-java-5.1.39.jar with timestamp 1512979434527

17/12/11 16:03:54 INFO AppClient$ClientEndpoint: Connecting to master spark://192.168.66.66:7077...

17/12/11 16:04:04 INFO SparkDeploySchedulerBackend: Connected to Spark cluster with app ID app-20171211160233-0013

17/12/11 16:04:04 INFO AppClient$ClientEndpoint: Executor added: app-20171211160233-0013/0 on worker-20171210231635-192.168.66.66-7078 (192.168.66.66:7078) with 2 cores

17/12/11 16:04:04 INFO SparkDeploySchedulerBackend: Granted executor ID app-20171211160233-0013/0 on hostPort 192.168.66.66:7078 with 2 cores, 1024.0 MB RAM

17/12/11 16:04:04 INFO AppClient$ClientEndpoint: Executor updated: app-20171211160233-0013/0 is now RUNNING

17/12/11 16:04:04 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 55147.

17/12/11 16:04:04 INFO NettyBlockTransferService: Server created on 55147

17/12/11 16:04:04 INFO BlockManagerMaster: Trying to register BlockManager

17/12/11 16:04:04 INFO BlockManagerMasterEndpoint: Registering block manager 172.20.107.151:55147 with 1122.0 MB RAM, BlockManagerId(driver, 172.20.107.151, 55147)

17/12/11 16:04:04 INFO BlockManagerMaster: Registered BlockManager

17/12/11 16:04:04 INFO SparkDeploySchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0

17/12/11 16:04:08 INFO SparkDeploySchedulerBackend: Registered executor NettyRpcEndpointRef(null) (xinfang:55156) with ID 0

17/12/11 16:04:08 INFO BlockManagerMasterEndpoint: Registering block manager xinfang:18681 with 511.1 MB RAM, BlockManagerId(0, xinfang, 18681)

17/12/11 16:04:08 INFO SparkContext: Starting job: show at jdbc.scala:18

17/12/11 16:04:08 INFO DAGScheduler: Got job 0 (show at jdbc.scala:18) with 1 output partitions

17/12/11 16:04:08 INFO DAGScheduler: Final stage: ResultStage 0 (show at jdbc.scala:18)

17/12/11 16:04:08 INFO DAGScheduler: Parents of final stage: List()

17/12/11 16:04:08 INFO DAGScheduler: Missing parents: List()

17/12/11 16:04:08 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at show at jdbc.scala:18), which has no missing parents

17/12/11 16:04:09 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 4.9 KB, free 1122.0 MB)

17/12/11 16:04:09 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 2.4 KB, free 1122.0 MB)

17/12/11 16:04:09 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 172.20.107.151:55147 (size: 2.4 KB, free: 1122.0 MB)

17/12/11 16:04:09 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006

17/12/11 16:04:09 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at show at jdbc.scala:18)

17/12/11 16:04:09 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks

17/12/11 16:04:09 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, xinfang, partition 0,PROCESS_LOCAL, 2069 bytes)

17/12/11 16:04:14 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on xinfang:18681 (size: 2.4 KB, free: 511.1 MB)

17/12/11 16:04:22 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 13334 ms on xinfang (1/1)

17/12/11 16:04:22 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool

17/12/11 16:04:22 INFO DAGScheduler: ResultStage 0 (show at jdbc.scala:18) finished in 13.369 s

17/12/11 16:04:23 INFO DAGScheduler: Job 0 finished: show at jdbc.scala:18, took 14.822540 s

+---+----+---+---+

| id|name|age|sex|

+---+----+---+---+

| 1| 信方| 26| 男|

| 2| 瑶瑶| 22| 女|

+---+----+---+---+

17/12/11 16:04:23 INFO SparkContext: Starting job: show at jdbc.scala:27

17/12/11 16:04:23 INFO DAGScheduler: Got job 1 (show at jdbc.scala:27) with 1 output partitions

17/12/11 16:04:23 INFO DAGScheduler: Final stage: ResultStage 1 (show at jdbc.scala:27)

17/12/11 16:04:23 INFO DAGScheduler: Parents of final stage: List()

17/12/11 16:04:23 INFO DAGScheduler: Missing parents: List()

17/12/11 16:04:23 INFO DAGScheduler: Submitting ResultStage 1 (MapPartitionsRDD[3] at show at jdbc.scala:27), which has no missing parents

17/12/11 16:04:23 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 4.9 KB, free 1122.0 MB)

17/12/11 16:04:23 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.4 KB, free 1122.0 MB)

17/12/11 16:04:23 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 172.20.107.151:55147 (size: 2.4 KB, free: 1122.0 MB)

17/12/11 16:04:23 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006

17/12/11 16:04:23 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 1 (MapPartitionsRDD[3] at show at jdbc.scala:27)

17/12/11 16:04:23 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks

17/12/11 16:04:23 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1, xinfang, partition 0,PROCESS_LOCAL, 2069 bytes)

17/12/11 16:04:24 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on xinfang:18681 (size: 2.4 KB, free: 511.1 MB)

17/12/11 16:04:24 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 1) in 425 ms on xinfang (1/1)

17/12/11 16:04:24 INFO DAGScheduler: ResultStage 1 (show at jdbc.scala:27) finished in 0.426 s

17/12/11 16:04:24 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool

17/12/11 16:04:24 INFO DAGScheduler: Job 1 finished: show at jdbc.scala:27, took 0.485020 s

+---+----+---+---+

| id|name|age|sex|

+---+----+---+---+

| 1| 信方| 26| 男|

| 2| 瑶瑶| 22| 女|

+---+----+---+---+

17/12/11 16:04:25 INFO SparkContext: Starting job: collect at jdbc.scala:29

17/12/11 16:04:25 INFO DAGScheduler: Got job 2 (collect at jdbc.scala:29) with 1 output partitions

17/12/11 16:04:25 INFO DAGScheduler: Final stage: ResultStage 2 (collect at jdbc.scala:29)

17/12/11 16:04:25 INFO DAGScheduler: Parents of final stage: List()

17/12/11 16:04:25 INFO DAGScheduler: Missing parents: List()

17/12/11 16:04:25 INFO DAGScheduler: Submitting ResultStage 2 (MapPartitionsRDD[5] at collect at jdbc.scala:29), which has no missing parents

17/12/11 16:04:25 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 5.0 KB, free 1122.0 MB)

17/12/11 16:04:25 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 2.4 KB, free 1122.0 MB)

17/12/11 16:04:25 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 172.20.107.151:55147 (size: 2.4 KB, free: 1122.0 MB)

17/12/11 16:04:25 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1006

17/12/11 16:04:25 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 2 (MapPartitionsRDD[5] at collect at jdbc.scala:29)

17/12/11 16:04:25 INFO TaskSchedulerImpl: Adding task set 2.0 with 1 tasks

17/12/11 16:04:25 INFO TaskSetManager: Starting task 0.0 in stage 2.0 (TID 2, xinfang, partition 0,PROCESS_LOCAL, 2069 bytes)

17/12/11 16:04:25 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on xinfang:18681 (size: 2.4 KB, free: 511.1 MB)

17/12/11 16:04:25 INFO TaskSetManager: Finished task 0.0 in stage 2.0 (TID 2) in 287 ms on xinfang (1/1)

17/12/11 16:04:25 INFO TaskSchedulerImpl: Removed TaskSet 2.0, whose tasks have all completed, from pool

17/12/11 16:04:25 INFO DAGScheduler: ResultStage 2 (collect at jdbc.scala:29) finished in 0.290 s

17/12/11 16:04:25 INFO DAGScheduler: Job 2 finished: collect at jdbc.scala:29, took 0.333871 s

[1,信方,26,男]

[2,瑶瑶,22,女]

17/12/11 16:04:26 INFO SparkContext: Starting job: collect at jdbc.scala:41

17/12/11 16:04:26 INFO DAGScheduler: Got job 3 (collect at jdbc.scala:41) with 1 output partitions

17/12/11 16:04:26 INFO DAGScheduler: Final stage: ResultStage 3 (collect at jdbc.scala:41)

17/12/11 16:04:26 INFO DAGScheduler: Parents of final stage: List()

17/12/11 16:04:26 INFO DAGScheduler: Missing parents: List()

17/12/11 16:04:26 INFO DAGScheduler: Submitting ResultStage 3 (MapPartitionsRDD[7] at collect at jdbc.scala:41), which has no missing parents

17/12/11 16:04:26 INFO MemoryStore: Block broadcast_3 stored as values in memory (estimated size 5.9 KB, free 1122.0 MB)

17/12/11 16:04:26 INFO MemoryStore: Block broadcast_3_piece0 stored as bytes in memory (estimated size 2.8 KB, free 1122.0 MB)

17/12/11 16:04:26 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on 172.20.107.151:55147 (size: 2.8 KB, free: 1122.0 MB)

17/12/11 16:04:26 INFO SparkContext: Created broadcast 3 from broadcast at DAGScheduler.scala:1006

17/12/11 16:04:26 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 3 (MapPartitionsRDD[7] at collect at jdbc.scala:41)

17/12/11 16:04:26 INFO TaskSchedulerImpl: Adding task set 3.0 with 1 tasks

17/12/11 16:04:26 INFO TaskSetManager: Starting task 0.0 in stage 3.0 (TID 3, xinfang, partition 0,PROCESS_LOCAL, 2069 bytes)

17/12/11 16:04:26 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on xinfang:18681 (size: 2.8 KB, free: 511.1 MB)

17/12/11 16:04:29 INFO TaskSetManager: Finished task 0.0 in stage 3.0 (TID 3) in 3053 ms on xinfang (1/1)

17/12/11 16:04:29 INFO TaskSchedulerImpl: Removed TaskSet 3.0, whose tasks have all completed, from pool

17/12/11 16:04:29 INFO DAGScheduler: ResultStage 3 (collect at jdbc.scala:41) finished in 3.055 s

17/12/11 16:04:29 INFO DAGScheduler: Job 3 finished: collect at jdbc.scala:41, took 3.101476 s

[96.0000000000,2015-08-18,深圳市宝安区石岩人民医院官田社区健康服务中心,宝安区,7.0000000000,113.947973,22.683914,25.0000000000]

[97.0000000000,2016-03-03,深圳市龙岗区第三人民医院,龙岗区,76.0000000000,114.2070007,22.65066798,367.0000000000]

[98.0000000000,2016-03-15,深圳市龙岗区第三人民医院,龙岗区,120.0000000000,114.2070007,22.65066798,439.0000000000]

[99.0000000000,2014-03-17,深圳市光明新区人民医院,光明新区,117.0000000000,113.914073,22.72181,637.0000000000]

[100.0000000000,2015-06-21,深圳市龙岗区南湾人民医院,龙岗区,84.0000000000,114.235159,22.732797,339.0000000000]

[101.0000000000,2015-12-28,深圳市福田区园岭医院上林社区健康服务中心,福田区,49.0000000000,114.06297,22.529945,78.0000000000]

[102.0000000000,2014-03-08,深圳市坪山新区人民医院,坪山新区,46.0000000000,114.357942,22.693397,165.0000000000]

[103.0000000000,2016-02-27,深圳市宝安区福永医院兴围社区健康服务中心,宝安区,65.0000000000,113.852402,22.70585,95.0000000000]

[104.0000000000,2016-03-04,深圳市宝安区松岗人民医院沙埔社区健康服务中心,宝安区,45.0000000000,113.855092,22.770395,63.0000000000]

[105.0000000000,2015-03-06,深圳市儿童医院,福田区,253.0000000000,114.0507065,22.5502964,864.0000000000]

17/12/11 16:04:29 INFO SparkContext: Invoking stop() from shutdown hook

17/12/11 16:04:29 INFO SparkUI: Stopped Spark web UI at http://172.20.107.151:4040

17/12/11 16:04:29 INFO SparkDeploySchedulerBackend: Shutting down all executors

17/12/11 16:04:29 INFO SparkDeploySchedulerBackend: Asking each executor to shut down

17/12/11 16:04:29 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!

17/12/11 16:04:29 INFO MemoryStore: MemoryStore cleared

17/12/11 16:04:29 INFO BlockManager: BlockManager stopped

17/12/11 16:04:29 INFO BlockManagerMaster: BlockManagerMaster stopped

17/12/11 16:04:29 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!

17/12/11 16:04:29 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.

17/12/11 16:04:29 INFO SparkContext: Successfully stopped SparkContext

17/12/11 16:04:29 INFO ShutdownHookManager: Shutdown hook called

17/12/11 16:04:30 INFO ShutdownHookManager: Deleting directory C:\Users\xinfang\AppData\Local\Temp\spark-318cb532-3e2f-44dd-bdc6-07637f0f37b6

17/12/11 16:04:30 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.

Process finished with exit code 0

sparksql处理mysql_Spark记录-SparkSQL远程操作MySQL和ORACLE相关推荐

  1. [python学习记录]python初步操作mysql

    数据库的连接 import MySQLdb # 创建连接对象里面,除了port必须是整数型,其余全是字符类型 conn = MySQLdb.connect(host = 'localhost',por ...

  2. SparkSQL之操作Mysql

    准备工作 我们准备使用sparksql数据库,然后使用TBLS表,这个TBLS保存了表的元数据信息. 操作Mysql数据表TBL val jdbcDF = spark.read.format(&quo ...

  3. MySQL行(记录)的详细操作

    一 介绍 MySQL数据操作: DML ======================================================== 在MySQL管理软件中,可以通过SQL语句中的 ...

  4. mysql 允许用户远程_Mysql 允许用户远程操作

    其实这个技术不难.我只是站在巨人的肩膀上.梳理一下我遇见的问题. 方法有两种.修改当前用户的host 为 %.或者直接授权(推荐) 直接授权: # mysql -u root -proot  // 登 ...

  5. mysql操作数据库的步骤,Golang操作MySql数据库的完整步骤记录

    前言 MySQL是业界常用的关系型数据库,在平时开发中会经常与MySql数据库打交道,所以在接下来将介绍怎么使用Go语言操作MySql数据库. 下载MySql连接驱动 Go语言中的database/s ...

  6. mysql 访问速度_操作mysql第一次访问速度慢（远程）

    最近在使用java操作远程的mysql数据库的时候,第一次请求非常的慢,而且极其容易引起系统的崩溃报错连接超时 下面就这个问题来解决下把 ------------------------------- ...

  7. DBeaver mySQL 远程操作数据库

    最近的项目需要用到mySQL,IDE准备用DBeaver,其优点不进行赘述.现在需要实现远程操作. 创建用户 首先需要进行用户的创建,原生的用户默认都是本地用户,可以通过更改的方式,也可以新建,这里我 ...

  8. MySQL练习记录——利用Python的pymysql模块操作MySQL数据库

    文章目录 前言 # 第一部分:数据库练习 准备数据 创建数据表 插入数据 SQL演练 1. SQL语句的强化 2. 创建"商品分类"表 3. 同步表数据 4. 创建"商品 ...

  9. 记录小白通过TCP/IP协议实现远程操作机械手臂

    记录小白通过TCP/IP协议实现远程操作机械手臂 作为一个本科,学大数据的菜狗.刚去实习就被分配到了硬件部,然后带我的那个老师让我去调试一下机械臂.但我计算机网络学的不好,加上紧张把一些基础的都忘了. ...

  10. MySQL 使用触发器记录用户的操作日志

    MySQL 使用触发器记录用户的操作日志 目录 MySQL 使用触发器记录用户的操作日志 一.创建用户数据表(emp)和保存操作日志的表(emp_log) 二.为 emp 表创建触发器 1.创建触发器 ...

最新文章

  1. 赵劲松：预知潜在风险，做化工安全科技创新的引领者
  2. tcp socket 异常关闭总结
  3. Android面试常问到的知识点
  4. 图解TC++3.0开发教程
  5. boost::describe模块宏BOOST_DESCRIBE_PP_IS_EMPTY的测试程序
  6. 制作U盘启动时【usb-hdd和usb-zip的区别】
  7. Object对象具体解释（二）之clone
  8. u8系统怎么连接服务器,用友U8 怎么连接远程服务器
  9. 基于Mac环境搭建以太坊私有区块链进行挖矿模拟
  10. 如何使用CodeBlocks开发C/C++程序
  11. Mac OS X10.11下CocoaPods的安装过程
  12. C# 类中的静态代码块
  13. 项目质量管理的几种常规方法
  14. Feed Ratios_usaco3.2_暴力
  15. mysql删除指令_mysql怎么用命令删除数据？
  16. 【USB笔记】USB 2.0 帧开始包Start-of-Frame Packets
  17. 《Python深度学习》第一部分读书笔记
  18. word右顶格,word文档最右边怎么对齐
  19. Excel学习——countif函数
  20. 月份加日期前面用on还是in_英语当中，年月日前加哪个介词on还是in；月日/年月的话呢？...

热门文章

  1. codeblocks 汉化包+汉化教程，仅需三步
  2. Apollo3.0 canbus代码解析（未完成，待修改）
  3. word宏、宏编程以及VBA
  4. MICROSOFT REPORTVIEWER（微软报表）项目中的应用
  5. mysql绿色版安装、局域网访问配置
  6. Manadata：用于数据管理的SPSS宏
  7. java链表实现多项式的运算
  8. [贪心][区间dp]Zero-One Codeforces1733D1D2
  9. Excel单元格自定义格式的知识和技巧
  10. python中文版-python有中文版吗