任务目标：
有一个informix数据库，其中有一个表有100万的数据，任务完成通过MapRed的方式将这100万数据导入到HDFS中，可以使用informix的分页sql达到并发查询数据库的目的。
任务开始：
1、编写MapRed的实现类起名称为InformixLoader。
大致代码如下
LOG.info("SqlMapper");
String url = context.getConfiguration().get("informix.url");
String[] str = value.toString().split("_");
long start = Long.parseLong(str[0]);
long length = Long.parseLong(str[1]);
Connection conn = null;
Statement st = null;
ResultSet rs = null;
String sql = "";
try {
Class.forName("com.informix.jdbc.IfxDriver");
conn = DriverManager.getConnection(url, "niosuser", "db");
st = conn.createStatement();
sql = "select skip " + start + " first " + length
+ " int_id from tpa_sts_cell_ne";
LOG.info("SqlMapper sql:" + sql);
rs = st.executeQuery(sql);
dataKey.set(value.toString());
Path file = new Path(StringUtils.unEscapeString(TMP_MAP_DIR
+ value.toString()));
FileSystem fs = file.getFileSystem(context.getConfiguration());
fs.createNewFile(file);
FSDataOutputStream output = fs.create(file);
LOG.info("SqlMapper createNewFile OK!");
while (rs.next()) {
String c1 = rs.getString(1)+"\n";
output.write(c1.getBytes());
output.flush();
}
output.close();
// fs.close();
data.set(value.toString());
context.write(dataKey, value);
LOG.info("SqlMapper OK!");
} catch (Exception e) {
throw new IOException(sql, e.fillInStackTrace());
} finally {
if (rs != null) {
try {
rs.close();
} catch (SQLException e) {
throw new IOException(e.fillInStackTrace());
}
}
if (st != null) {
try {
st.close();
} catch (SQLException e) {
throw new IOException(e.fillInStackTrace());
}
}
if (conn != null) {
try {
conn.close();
} catch (SQLException e) {
throw new IOException(e.fillInStackTrace());
}
}
}
2、编写InputFormater类
代码如下：
LOG.info("InputFormarter");
String url = context.getConfiguration().get("informix.url");
Connection conn = null;
Statement st = null;
ResultSet rs = null;
try {
Class.forName("com.informix.jdbc.IfxDriver");
conn = DriverManager.getConnection(url, "niosuser", "db");
st = conn.createStatement();
String sql = "select count(*) from tpa_sts_cell_ne";
rs = st.executeQuery(sql);
rs.next();
int count = rs.getInt(1);
List<InputSplit> splits = new ArrayList<InputSplit>();
int size = 50000;
int inv = count / size;
int last = count % size;
for (int i = 0; i < inv; i++) {
SqlSplit s = new SqlSplit(i * size, size);
splits.add(s);
}
if (last!=0){
SqlSplit s = new SqlSplit(inv * size, last);
splits.add(s);
}
return splits;
} catch (Exception e) {
throw new IOException(e.fillInStackTrace());
} finally {
if (rs != null) {
try {
rs.close();
} catch (SQLException e) {
throw new IOException(e.fillInStackTrace());
}
}
if (st != null) {
try {
st.close();
} catch (SQLException e) {
throw new IOException(e.fillInStackTrace());
}
}
if (conn != null) {
try {
conn.close();
} catch (SQLException e) {
throw new IOException(e.fillInStackTrace());
}
}
}
3、编写reducer类
大致代码如下
String keyStr = key.toString();
Path outFile = new Path(StringUtils.unEscapeString(TMP_RED_DIR
+ keyStr));
LOG.info("SqlReducer outfile:"+outFile.getName());
FileSystem outfs = outFile
.getFileSystem(context.getConfiguration());
outfs.createNewFile(outFile);
FSDataOutputStream output = outfs.create(outFile);
for (Text val : values) {
LOG.info("SqlReducer");
String str = val.toString();
LOG.info("file:"+str);
Path inputFile = new Path(StringUtils
.unEscapeString(TMP_MAP_DIR + str));
FileSystem fs = inputFile.getFileSystem(context
.getConfiguration());
FSDataInputStream input = fs.open(inputFile);
BufferedInputStream bi = new BufferedInputStream(input);
byte[] buffer=new byte[1024];
int length=bi.read(buffer);
while (length!=-1) {
if (length==1024){
output.write(buffer);
}else{
byte[] tmp=new byte[length];
for(int i=0;i<tmp.length;i++){
tmp[i]=buffer[i];
}
output.write(buffer);
}
length=bi.read(buffer);
}
bi.close();
input.close();
// fs.close();
output.flush();
}
output.close();
result.set(key.toString());
context.write(key, result);
4、编写outformat类
大致代码如下：
Path outFilePath = getDefaultWorkFile(context, "");
final FileSystem fs = outFilePath.getFileSystem(context
.getConfiguration());
final FSDataOutputStream output = fs.create(outFilePath);
return new RecordWriter<Text, Text>() {
@Override
public void close(TaskAttemptContext context)
throws IOException, InterruptedException {
output.flush();
output.close();
// fs.close();
}
@Override
public void write(Text key, Text value) throws IOException,
InterruptedException {
LOG.info("RecordWriter filename:"+value.toString());
Path file = new Path(StringUtils.unEscapeString(TMP_RED_DIR
+ value.toString()));
FileSystem fs = file.getFileSystem(context
.getConfiguration());
FSDataInputStream input = fs.open(file);
BufferedInputStream bi = new BufferedInputStream(input);
byte[] buffer=new byte[1024];
int length=bi.read(buffer);
while (length!=-1) {
if (length==1024){
output.write(buffer);
}else{
byte[] tmp=new byte[length];
for(int i=0;i<tmp.length;i++){
tmp[i]=buffer[i];
}
output.write(buffer);
}
length=bi.read(buffer);
}
bi.close();
input.close();
// fs.close();
}
};
5、编写启动代码
大致代码如下：
File jarFile = EJob.createTempJar("bin");
EJob.addClasspath("I:\\work\\hadoop\\hadoop\\hadoop-site.xml");
ClassLoader classLoader = EJob.getClassLoader();
Thread.currentThread().setContextClassLoader(classLoader);
args = new String[] { "/tmp/sqlloader10/" };
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args)
.getRemainingArgs();
if (otherArgs.length != 1) {
System.err.println("Usage: informixLoader <out>");
System.exit(2);
}
conf
.set("informix.url",
"jdbc:informix-sqli://10.0.2.36:8001/niosdb:INFORMIXSERVER=niosserver");
Job job = new Job(conf, "informix loader");
// And add this statement. XXX
((JobConf) job.getConfiguration()).setJar(jarFile.toString());
job.setInputFormatClass(InputFormarter.class);
job.setJarByClass(InformixLoader.class);
job.setMapperClass(SqlMapper.class);
job.setReducerClass(SqlReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
job.setOutputFormatClass(OutputFormater.class);
// FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[0]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
5、详细分析后续说明