• java注释代码规范


    //收集了一小部分,忘记的时候过来查一下

    java--hadoop部分

    /**
    * 此类用来处理DNS原始日志:统计给定域名平均响应时延
    * @param Input
    * @param Output
    * @param cacheUriListfilePath
    * @param cacheIpNetTypefilePath
    * <br>[文件cachefile需要上传HDFS,文件为K-V形式,多个V用;隔开]</br>
    * 
    * <P><B>NOTE:</B>该类适合限定域名的时延统计,若统计所有域名的的平均时延此类不适用,因为reducer类使用集合进行汇聚,所有域名会导致内存溢出</p>
    */

    <P>是单独起个段落 (注意和<br>换行、<pre>再起一个段落 比较)
    <B>是加黑加粗
    @param是参数
    @author yanghl 作者

    /**
    * This is an example Aggregated Hadoop Map/Reduce application. Computes the
    * histogram of the words in the input texts.
    * 
    * To run: bin/hadoop jar hadoop-*-examples.jar aggregatewordhist <i>in-dir</i>
    * <i>out-dir</i> <i>numOfReducers</i> textinputformat
    * 
    */

    <i>是倾斜体,表示路径

    /**
    * Creates a <code>Statement</code> object for sending
    * SQL statements to the database.
    * SQL statements without parameters are normally
    * executed using <code>Statement</code> objects. If the same SQL statement
    * is executed many times, it may be more efficient to use a
    * <code>PreparedStatement</code> object.
    * <P>
    * Result sets created using the returned <code>Statement</code>
    * object will by default be type <code>TYPE_FORWARD_ONLY</code>
    * and have a concurrency level of <code>CONCUR_READ_ONLY</code>.
    * The holdability of the created result sets can be determined by
    * calling {@link #getHoldability}.
    *
    * @return a new default <code>Statement</code> object
    * @exception SQLException if a database access error occurs
    * or this method is called on a closed connection
    */

    @return
    @exception
    {@link #getHoldability}.加链接 getHoldability()本包的一个方法

    /** Holds a &lt;url, referrer, time &gt; tuple */
    static class AccessRecord implements Writable, DBWritable {.....}

    ========================
    &lt; &gt;注释中的<>表示的另一种方法
    ========================

    /**
    * <P>The basic service for managing a set of JDBC drivers.<br>
    * <B>NOTE:</B> The {@link <code>DataSource</code>} interface, new in the
    * JDBC 2.0 API, provides another way to connect to a data source.
    * The use of a <code>DataSource</code> object is the preferred means of
    * connecting to a data source.
    *
    * <P>As part of its initialization, the <code>DriverManager</code> class will
    * attempt to load the driver classes referenced in the "jdbc.drivers"
    * system property. This allows a user to customize the JDBC Drivers
    * used by their applications. For example in your
    * ~/.hotjava/properties file you might specify:
    * <pre>
    * <CODE>jdbc.drivers=foo.bah.Driver:wombat.sql.Driver:bad.taste.ourDriver</CODE>
    * </pre>
    */

    ===============================
    【br、P、pre、code、B】标签
    <br>换行
    <pre>再起一个段落
    ===============================

    /**
    * A tool interface that supports handling of generic command-line options.
    * 
    * <p><code>Tool</code>, is the standard for any Map-Reduce tool/application. 
    * The tool/application should delegate the handling of 
    * <a href="{@docRoot}/../hadoop-project-dist/hadoop-common/CommandsManual.html#Generic_Options">
    * standard command-line options</a> to {@link ToolRunner#run(Tool, String[])} 
    * and only handle its custom arguments.</p>
    * 
    * <p>Here is how a typical <code>Tool</code> is implemented:</p>
    * <p><blockquote><pre>
    * public class MyApp extends Configured implements Tool {
    * 
    * public int run(String[] args) throws Exception {
    * // <code>Configuration</code> processed by <code>ToolRunner</code>
    * Configuration conf = getConf();
    * 
    * // Create a JobConf using the processed <code>conf</code>
    * JobConf job = new JobConf(conf, MyApp.class);
    * 
    * // Process custom command-line options
    * Path in = new Path(args[1]);
    * Path out = new Path(args[2]);
    * 
    * // Specify various job-specific parameters 
    * job.setJobName("my-app");
    * job.setInputPath(in);
    * job.setOutputPath(out);
    * job.setMapperClass(MyMapper.class);
    * job.setReducerClass(MyReducer.class);
    *
    * // Submit the job, then poll for progress until the job is complete
    * JobClient.runJob(job);
    * return 0;
    * }
    * 
    * public static void main(String[] args) throws Exception {
    * // Let <code>ToolRunner</code> handle generic command-line options 
    * int res = ToolRunner.run(new Configuration(), new MyApp(), args);
    * 
    * System.exit(res);
    * }
    * }
    * </pre></blockquote></p>
    * 
    * @see GenericOptionsParser
    * @see ToolRunner
    */

    @InterfaceAudience.Public
    @InterfaceStability.Stable
    public interface Tool extends Configurable {
    【<p><blockquote><pre>】

    还可以在代码注释里画表格、列表

    /**
    * Rounding mode to round away from zero. Always increments the
    * digit prior to a non-zero discarded fraction. Note that this
    * rounding mode never decreases the magnitude of the calculated
    * value.
    *
    *<p>Example:
    *<table border>
    *<tr valign=top><th>Input Number</th>
    * <th>Input rounded to one digit<br> with {@code UP} rounding
    *<tr align=right><td>5.5</td> <td>6</td>
    *<tr align=right><td>2.5</td> <td>3</td>
    *<tr align=right><td>1.6</td> <td>2</td>
    *<tr align=right><td>1.1</td> <td>2</td>
    *<tr align=right><td>1.0</td> <td>1</td>
    *<tr align=right><td>-1.0</td> <td>-1</td>
    *<tr align=right><td>-1.1</td> <td>-2</td>
    *<tr align=right><td>-1.6</td> <td>-2</td>
    *<tr align=right><td>-2.5</td> <td>-3</td>
    *<tr align=right><td>-5.5</td> <td>-6</td>
    *</table>
    */
    <ul>
    <li>a</li>
    <li>a</li>
    <li>a</li>
    </ul>

    还可以在代码注释里【写代码或配置文件内容】{@code xxxx....}

    /**
    * This program uses map/reduce to just run a distributed job where there is
    * no interaction between the tasks and each task write a large unsorted
    * random binary sequence file of BytesWritable.
    * In order for this program to generate data for terasort with 10-byte keys
    * and 90-byte values, have the following config:
    * <pre>{@code
    * <?xml version="1.0"?>
    * <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
    * <configuration>
    * <property>
    * <name>mapreduce.randomwriter.minkey</name>
    * <value>10</value>
    * </property>
    * <property>
    * <name>mapreduce.randomwriter.maxkey</name>
    * <value>10</value>
    * </property>
    * <property>
    * <name>mapreduce.randomwriter.minvalue</name>
    * <value>90</value>
    * </property>
    * <property>
    * <name>mapreduce.randomwriter.maxvalue</name>
    * <value>90</value>
    * </property>
    * <property>
    * <name>mapreduce.randomwriter.totalbytes</name>
    * <value>1099511627776</value>
    * </property>
    * </configuration>}</pre>
    * Equivalently, {@link RandomWriter} also supports all the above options
    * and ones supported by {@link GenericOptionsParser} via the command-line.
    */
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  • 原文地址:https://www.cnblogs.com/yanghaolie/p/7029207.html
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