[15] | 1 | /** |
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| 2 | * Program: HBaseRecord.java |
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| 3 | * Editor: Waue Chen |
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| 4 | * From : NCHC. Taiwn |
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| 5 | * Last Update Date: 06/01/2008 |
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| 6 | */ |
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| 7 | |
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| 8 | /** |
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| 9 | * Purpose : |
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| 10 | * Parse your record and then store in HBase. |
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| 11 | * |
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| 12 | * HowToUse : |
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| 13 | * Make sure Hadoop file system and Hbase are running correctly. |
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| 14 | * 1. put test.txt in t1 directory which content is |
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[16] | 15 | --------------- |
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| 16 | name:locate:years |
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| 17 | waue:taiwan:1981 |
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| 18 | shellon:taiwan:1981 |
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| 19 | --------------- |
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[15] | 20 | * 2. hadoop_root/$ bin/hadoop dfs -put t1 t1 |
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| 21 | * 3. hbase_root/$ bin/hbase shell |
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| 22 | * 4. hql > create table t1_table("person"); |
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| 23 | * 5. Come to Eclipse and run this code, and we will let database as that |
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[16] | 24 | t1_table -> person |
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| 25 | ---------------- |
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| 26 | | name | locate | years | |
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| 27 | | waue | taiwan | 1981 | |
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| 28 | | shellon | taiwan | 1981 | |
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| 29 | ---------------- |
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[15] | 30 | * Check Result: |
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| 31 | * Go to hbase console, type : |
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| 32 | * hql > select * from t1_table; |
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[16] | 33 | 08/06/06 12:20:48 INFO hbase.HTable: Creating scanner over t1_table starting at key |
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| 34 | +-------------------------+-------------------------+-------------------------+ |
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| 35 | | Row | Column | Cell | |
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| 36 | +-------------------------+-------------------------+-------------------------+ |
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| 37 | | 0 | person:locate | locate | |
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| 38 | +-------------------------+-------------------------+-------------------------+ |
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| 39 | | 0 | person:name | name | |
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| 40 | +-------------------------+-------------------------+-------------------------+ |
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| 41 | | 0 | person:years | years | |
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| 42 | +-------------------------+-------------------------+-------------------------+ |
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| 43 | | 19 | person:locate | taiwan | |
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| 44 | +-------------------------+-------------------------+-------------------------+ |
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| 45 | | 19 | person:name | waue | |
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| 46 | +-------------------------+-------------------------+-------------------------+ |
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| 47 | | 19 | person:years | 1981 | |
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| 48 | +-------------------------+-------------------------+-------------------------+ |
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| 49 | | 36 | person:locate | taiwan | |
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| 50 | +-------------------------+-------------------------+-------------------------+ |
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| 51 | | 36 | person:name | shellon | |
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| 52 | +-------------------------+-------------------------+-------------------------+ |
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| 53 | | 36 | person:years | 1981 | |
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| 54 | +-------------------------+-------------------------+-------------------------+ |
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| 55 | 3 row(s) in set. (0.04 sec) |
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[15] | 56 | */ |
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| 57 | |
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| 58 | package tw.org.nchc.code; |
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| 59 | |
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| 60 | import java.io.BufferedReader; |
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| 61 | import java.io.BufferedWriter; |
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| 62 | import java.io.File; |
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[16] | 63 | import java.io.FileOutputStream; |
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[15] | 64 | import java.io.FileReader; |
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| 65 | import java.io.FileWriter; |
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| 66 | import java.io.IOException; |
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| 67 | import java.util.Iterator; |
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| 68 | import org.apache.hadoop.fs.FileSystem; |
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| 69 | import org.apache.hadoop.fs.Path; |
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| 70 | import org.apache.hadoop.hbase.io.ImmutableBytesWritable; |
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| 71 | import org.apache.hadoop.hbase.mapred.TableReduce; |
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| 72 | import org.apache.hadoop.io.LongWritable; |
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| 73 | import org.apache.hadoop.io.MapWritable; |
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| 74 | import org.apache.hadoop.io.Text; |
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| 75 | import org.apache.hadoop.mapred.JobClient; |
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| 76 | import org.apache.hadoop.mapred.JobConf; |
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| 77 | import org.apache.hadoop.mapred.OutputCollector; |
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| 78 | import org.apache.hadoop.mapred.Reporter; |
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| 79 | import org.apache.hadoop.mapred.lib.IdentityMapper; |
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| 80 | import org.apache.hadoop.mapred.lib.IdentityReducer; |
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| 81 | |
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| 82 | |
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[16] | 83 | |
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| 84 | class ReduceClass extends TableReduce<LongWritable, Text> { |
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| 85 | // on this sample, map is nonuse, we use reduce to handle |
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| 86 | public void reduce(LongWritable key, Iterator<Text> values, |
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| 87 | OutputCollector<Text, MapWritable> output, Reporter reporter) |
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| 88 | throws IOException { |
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| 89 | String sp = ":"; |
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| 90 | String bf = "person:"; |
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| 91 | // this map holds the columns per row |
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| 92 | MapWritable map = new MapWritable(); |
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| 93 | // values.next().getByte() can get value and transfer to byte form, |
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| 94 | String stro = new String(values.next().getBytes()); |
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| 95 | String str[] = stro.split(sp); |
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| 96 | |
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| 97 | BufferedReader fconf = new BufferedReader(new FileReader(new File("/tmp/fi_conf.tmp"))); |
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| 98 | // int length = cf.length; |
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| 99 | |
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| 100 | |
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| 101 | |
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| 102 | // test for debug |
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| 103 | FileOutputStream out = new FileOutputStream(new File( |
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| 104 | "/home/waue/mr-result.txt")); |
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| 105 | String first_line = fconf.readLine(); |
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| 106 | |
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| 107 | // test for debug |
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| 108 | String[] cf = first_line.split(sp); |
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| 109 | int length = cf.length; |
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| 110 | for(int i=0 ; i<length; i ++){ |
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| 111 | out.write((bf + cf[i]+"\n").getBytes()); |
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| 112 | |
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| 113 | } |
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| 114 | out.close(); |
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| 115 | // Column id is created dymanically, |
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| 116 | Text[] col_n = new Text[length]; |
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| 117 | byte[][] b_l = new byte[length][]; |
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| 118 | // contents must be ImmutableBytesWritable |
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| 119 | ImmutableBytesWritable[] w_l = new ImmutableBytesWritable[length]; |
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| 120 | map.clear(); |
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| 121 | |
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| 122 | for (int i = 0; i < length; i++) { |
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| 123 | col_n[i] = new Text(bf + cf[i]); |
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| 124 | b_l[i] = str[i].getBytes(); |
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| 125 | w_l[i] = new ImmutableBytesWritable(b_l[i]); |
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| 126 | // populate the current row |
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| 127 | map.put(col_n[i], w_l[i]); |
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| 128 | } |
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| 129 | // add the row with the key as the row id |
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| 130 | output.collect(new Text(key.toString()), map); |
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| 131 | } |
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| 132 | } |
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| 133 | |
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[15] | 134 | public class HBaseRecordPro { |
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| 135 | |
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| 136 | /* Denify parameter */ |
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[16] | 137 | |
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[15] | 138 | // file path in hadoop file system (not phisical file system) |
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[16] | 139 | final String file_path = "/home/waue/test.txt"; |
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| 140 | |
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[15] | 141 | // setup MapTask and Reduce Task |
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| 142 | |
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[16] | 143 | final String bf = "person:"; |
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[15] | 144 | |
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[16] | 145 | final String table_name = "testend"; |
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| 146 | |
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| 147 | final String sp = ":"; |
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| 148 | |
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| 149 | String[] cf ; |
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[15] | 150 | |
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[16] | 151 | String test; |
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[15] | 152 | |
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[16] | 153 | public HBaseRecordPro() { |
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[15] | 154 | |
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| 155 | |
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| 156 | } |
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[16] | 157 | public HBaseRecordPro(String[] st) { |
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| 158 | cf = st; |
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| 159 | } |
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[15] | 160 | |
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[16] | 161 | static public String parseFirstLine(String in, String ou) throws IOException { |
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[15] | 162 | BufferedReader fi = new BufferedReader(new FileReader(new File(in))); |
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[16] | 163 | BufferedWriter ff = new BufferedWriter(new FileWriter(new File("/tmp/fi_conf.tmp"))); |
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[15] | 164 | BufferedWriter fw = new BufferedWriter(new FileWriter(new File(ou))); |
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[16] | 165 | String first_line, data; |
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[15] | 166 | first_line = fi.readLine(); |
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[16] | 167 | ff.write(first_line); |
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| 168 | ff.flush(); |
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| 169 | do { |
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[15] | 170 | data = fi.readLine(); |
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[16] | 171 | if (data == null) { |
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[15] | 172 | break; |
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[16] | 173 | } else { |
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| 174 | fw.write(data + "\n"); |
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| 175 | fw.flush(); |
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[15] | 176 | } |
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[16] | 177 | } while (true); |
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[15] | 178 | fw.close(); |
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[16] | 179 | ff.close(); |
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[15] | 180 | return first_line; |
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| 181 | } |
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[16] | 182 | |
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[15] | 183 | /** |
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| 184 | * Runs the demo. |
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| 185 | */ |
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| 186 | public static void main(String[] args) throws IOException { |
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| 187 | |
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[16] | 188 | String bf = "person:"; |
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| 189 | String file_path = "/home/waue/test.txt"; |
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| 190 | |
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[15] | 191 | final String file_tmp = "/tmp/HBaseRecord.text.tmp"; |
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| 192 | final int mapTasks = 1; |
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| 193 | final int reduceTasks = 1; |
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[16] | 194 | String[] column_family = { bf }; |
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[15] | 195 | |
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| 196 | HBaseRecordPro setup = new HBaseRecordPro(); |
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| 197 | |
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[16] | 198 | String first_line = parseFirstLine(file_path, file_tmp); |
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[15] | 199 | System.out.println(first_line); |
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[16] | 200 | // HBaseRecordPro.cf = first_line.split(sp); |
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[15] | 201 | |
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[16] | 202 | |
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| 203 | // test |
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| 204 | /* |
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| 205 | for (int i = 0; i < 3; i++) { |
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| 206 | System.out.println("column[" + i + "]=" + bf + cf[i]); |
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| 207 | }*/ |
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| 208 | |
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| 209 | BuildHTable build_table = new BuildHTable(setup.table_name, |
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| 210 | column_family); |
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[15] | 211 | if (!build_table.checkTableExist(setup.table_name)) { |
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| 212 | if (!build_table.createTable()) { |
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| 213 | System.out.println("create table error !"); |
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| 214 | } |
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| 215 | } else { |
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| 216 | System.out.println("Table \"" + setup.table_name |
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| 217 | + "\" has already existed !"); |
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[16] | 218 | } |
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[15] | 219 | JobConf conf = new JobConf(HBaseRecordPro.class); |
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| 220 | FileSystem fileconf = FileSystem.get(conf); |
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[16] | 221 | fileconf.copyFromLocalFile(true, new Path(file_tmp), new Path(file_tmp)); |
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| 222 | // Job name; you can modify to any you like |
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[15] | 223 | conf.setJobName("PersonDataBase"); |
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| 224 | |
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| 225 | // Hbase table name must be correct , in our profile is t1_table |
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| 226 | TableReduce.initJob(setup.table_name, ReduceClass.class, conf); |
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| 227 | |
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| 228 | // below are map-reduce profile |
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| 229 | conf.setNumMapTasks(mapTasks); |
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| 230 | conf.setNumReduceTasks(reduceTasks); |
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| 231 | conf.setInputPath(new Path(file_tmp)); |
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| 232 | conf.setMapperClass(IdentityMapper.class); |
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| 233 | conf.setCombinerClass(IdentityReducer.class); |
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| 234 | conf.setReducerClass(ReduceClass.class); |
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[16] | 235 | |
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[15] | 236 | JobClient.runJob(conf); |
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| 237 | |
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| 238 | } |
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[16] | 239 | } |
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