<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[bit1010的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/bit1010</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; bit1010]]></copyright><item><title><![CDATA[[【Linux命令003】ln建立软链接]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/50903698</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/50903698</guid><author>bit1010</author><pubDate>Wed, 16 Mar 2016 11:39:41 +0800</pubDate><description><![CDATA[命令


ln -s 原文件 目标文件(快捷方式)


在spark的配置文件目录下建立对hive-site.xml的软链：


cd $SPARK_HOME/conf


ln -s $HIVE_HOME/conf/hive-site.xml hive-site.xml]]></description><category></category></item><item><title><![CDATA[【Linux命令002】tr命令]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/50895622</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/50895622</guid><author>bit1010</author><pubDate>Tue, 15 Mar 2016 13:18:37 +0800</pubDate><description><![CDATA[tr命令的含义是translate，


hostname | tr [a-z] [A-Z]
命令结果是将hostname所有字母转换为大写]]></description><category></category></item><item><title><![CDATA[【Linux命令001】cp命令]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/50895557</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/50895557</guid><author>bit1010</author><pubDate>Tue, 15 Mar 2016 13:15:47 +0800</pubDate><description><![CDATA[cp命令用于复制文件或者文件目录到目标目录


假如目录结构如下：


src目录
   a.log
   b.log


target目录



那么：cp src target



1.]]></description><category></category></item><item><title><![CDATA[SparkSQL10_Unsafe相关_01_sun.misc.Unsafe]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/49334639</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/49334639</guid><author>bit1010</author><pubDate>Thu, 22 Oct 2015 15:57:04 +0800</pubDate><description><![CDATA[1. Unsafe.copyMemory
1.1 如下代码实现字节数组的拷贝

import sun.misc.Unsafe;

import java.lang.reflect.Field;

public class UnsafeTest {
    private static final Unsafe _UNSAFE;
    private static final int BYT]]></description><category></category></item><item><title><![CDATA[SparkSQL08_SQLCommand_02_DescribeTable]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/49176299</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/49176299</guid><author>bit1010</author><pubDate>Fri, 16 Oct 2015 11:12:37 +0800</pubDate><description><![CDATA[1. 执行如下SQL命令
      sc.textFile("file:///D:\\myprojects\\SparkSQLPerf\\data\\students.txt")
      .map(x => x.split(" "))
      .map(x => (Student3(x(0), x(1), x(3), x(2).toInt))).toDF().registerTempT]]></description><category></category></item><item><title><![CDATA[SparkSQL07_ThriftServer_01_SparkThriftServer环境搭建]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/49126371</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/49126371</guid><author>bit1010</author><pubDate>Wed, 14 Oct 2015 15:58:44 +0800</pubDate><description><![CDATA[1. 首先安装Hive并且保证已经启动了Hive Meta Store Service
如果没有启动Hive Meta Store Service，那么hive-site.xml文件中如下配置的通过thrift访问metastore server将无法建立连接，也就是9083端口没有监听


  
    hive.metastore.uris
    thrift://0.0.0.0:9]]></description><category></category></item><item><title><![CDATA[SparkSQL00_总体介绍_04_Scala Type与Catalyst Type类型转换(第一部分)]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/49022155</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/49022155</guid><author>bit1010</author><pubDate>Sat, 10 Oct 2015 11:59:53 +0800</pubDate><description><![CDATA[1. Scala Type和Catalyst Type的转换包括简单类型，比如String，Date, Number之间的转换；也包括集合类型，如Array、Map之间的转换。


2. Scala Type， CatalystType指的是什么
ScalaType指的是Scala和Java语言提供的数据类型，比如String, Date,Decimal，Array,Map等。
Cata]]></description><category></category></item><item><title><![CDATA[SparkSQL05_prepareForExecution_01_EnsureRequirements]]></title><link>https://blog.youkuaiyun.com/bit1010/article/details/48970995</link><guid>https://blog.youkuaiyun.com/bit1010/article/details/48970995</guid><author>bit1010</author><pubDate>Thu, 08 Oct 2015 12:35:50 +0800</pubDate><description><![CDATA[源代码：


/**
 * Ensures that the [[org.apache.spark.sql.catalyst.plans.physical.Partitioning Partitioning]]
 * of input data meets the
 * [[org.apache.spark.sql.catalyst.plans.physical.Distribution D]]></description><category></category></item></channel></rss>