前言:
mysql a表是按照分库存储的,现在需要抽取到hdfs中
实现点:
1 自定义DBInputFormat,将表对应的分库重新创建conn连接,然后切片
2 在mapper类中自定义切片后的接收数据的接收类
3 在mapper中得到数据写出去
sqoop.properties文件如下:
driverName=com.mysql.jdbc.Driver globaldb=jdbc:mysql://192.168.8.177:3306/mydb?tinyInt1isBit=false dbProcInstances=jdbc:mysql://192.168.1.39:3306/mydb[1~64],192.168.1.42:3306/mydb[1~64],192.168.1.133:3306/mydb[65~128],192.168.1.136:3306/mydb[65~128] mysqlUser=root mysqlPw=testhive maxSplitRowsCount=50000 dbUrlConnProps=tinyInt1isBit=false jobName=coursewares_content.2016-08-21@testhive outPutPath=/user/bigdata/tmp/tmp_ct_teach_coursewares_content query=select coursewares_id,belong_type,content,school_id from ct_teach_coursewares_content queryCount=SELECT COUNT(1) FROM ct_teach_coursewares_content tableIsSharding=true
代码:
主类:
import com.xuele.bigdata.config.Config; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.io.Writable; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.lib.db.DBConfiguration; import org.apache.hadoop.mapreduce.lib.db.DBWritable; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import java.io.DataInput; import java.io.DataOutput; import java.io.IOException; import java.sql.PreparedStatement; import java.sql.ResultSet; import java.sql.ResultSetMetaData; import java.sql.SQLException; import java.util.HashMap; import java.util.Map; /** * Created by zm on 16/7/12. */ public class ShardingDB { /** * commonRecord */ public static class CommonRecord implements Writable, DBWritable { private String[] fields; // 列名 数组 private String fieldsStr; // 列之间用,间隔的字符串 private Map<String,Object> kv=new HashMap<String,Object>(); // 类名和列值的 map集合 public CommonRecord() { } public String[] getFields(){ return fields; } public void readFields(DataInput in) throws IOException { fieldsStr=Text.readString(in); // 得到列名 中间用,间隔 fields=fieldsStr.split(","); // 将 从写入的列名中去kv map里获取列值 for(String f:fields){ kv.put(f, Text.readString(in)); } } public void write(DataOutput out) throws IOException { Text.writeString(out,fieldsStr); // 写出列名的组合 中间用,间隔 for(String f:fields){ // 写出列值 Text.writeString(out, kv.get(f).toString()); } } public void readFields(ResultSet result) throws SQLException { ResultSetMetaData metaData=result.getMetaData(); // 获取元数据 int num=metaData.getColumnCount(); fields=new String[num]; fieldsStr=""; for(int i=1;i<=num;i++){ fieldsStr+=metaData.getColumnLabel(i)+","; // 得到列名 kv.put(metaData.getColumnLabel(i),result.getObject(i)); // 将 <列名,列值> 放在 Map中 } fieldsStr=fieldsStr.substring(0,fieldsStr.length()-1); fields=fieldsStr.split(","); // 得到列名的数组 } public void write(PreparedStatement stmt) throws SQLException { int i=1; for(String f:fields){ stmt.setObject(i++, kv.get(f)); // 将数组中的列遍历,然后去 map中获取列名对应的value值 } } public String toString() { StringBuilder sb=new StringBuilder(); for(String f:fields){ if (kv.get(f) != null) { // 将列值中的换行符用空格替代 列之间用\001间隔 sb.append(kv.get(f).toString().replace("\r\n\n","").replace("\r\n", "").replace("\n", " ").replace("\r"," ").replace("\001","")).append("\001"); } else { sb.append("").append("\001"); } } sb.deleteCharAt(sb.length()-1); return sb.toString(); } } public static class DBInputMapper extends Mapper<LongWritable, CommonRecord,NullWritable,Text>{ public void map(LongWritable key, CommonRecord value,Context context) throws IOException, InterruptedException { context.write(NullWritable.get(), new Text(value.toString())); //Thread.sleep(12000); } } public static void main(String[] args) throws Exception{ try { if (args.length == 1) { Config propertiesConfig = new Config(); propertiesConfig.init(args[0]); String globaldb = propertiesConfig.getValue("globaldb"); // jdbc:mysql://192.168.1.39:3306/mydb String dbProcInstances = propertiesConfig.getValue("dbProcInstances"); // jdbc:mysql://192.168.1.39:3306/,192.168.1.42:3306 String dbUrlConnProps = propertiesConfig.getValue("dbUrlConnProps"); // tinyInt1isBit=false String driverName = propertiesConfig.getValue("driverName");// com.mysql.jdbc.Driver String mysqlUser = propertiesConfig.getValue("mysqlUser");// root String mysqlPw = propertiesConfig.getValue("mysqlPw"); // testhive String tableIsSharding = propertiesConfig.getValue("tableIsSharding"); // true or fasle String jobName = propertiesConfig.getValue("jobName");// ShardingDBTest String outPutPath = propertiesConfig.getValue("outPutPath");// / String maxSplitRowsCount = propertiesConfig.getValue("maxSplitRowsCount", "5000"); String inputQuery = propertiesConfig.getValue("query"); String inputCountQuery = propertiesConfig.getValue("queryCount"); Configuration conf = new Configuration(); conf.setBoolean("tableIsSharding", Boolean.parseBoolean(tableIsSharding)); conf.set("globaldb", globaldb); // 单片库 conf.set("dbProcInstances", dbProcInstances); // 分片库 conf.set("dbUrlConnProps", dbUrlConnProps); // 分片库 增加针对 tinyiint类型的转义 conf.set("maxSplitRowsCount", maxSplitRowsCount); // 分片行数 DBConfiguration.configureDB(conf, driverName, globaldb, mysqlUser, mysqlPw); // 使用hadoop的类连接 关系型数据库 Job job = Job.getInstance(conf, ShardingDB.class.getName()); job.setJobName(jobName); job.setNumReduceTasks(1); job.setJarByClass(ShardingDB.class); job.setInputFormatClass(ShardingDBInputFormat.class); // 自定义 分片读取数据规则, 主要针对 jdbc:mysql://192.168.1.39:3306/,192.168.1.42:3306/ 这种的进行读取数据并写出去 job.setMapperClass(DBInputMapper.class); // 自定义 Mapper类 job.setMapOutputKeyClass(NullWritable.class); // 设置map输出key类型 job.setMapOutputValueClass(Text.class); // 设置map输出value类型 job.setNumReduceTasks(10); FileOutputFormat.setOutputPath(job, new Path(outPutPath)); // 设置输出目录 ShardingDBInputFormat.setInput(job, CommonRecord.class, inputQuery, inputCountQuery); // System.exit(job.waitForCompletion(true) ? 0 : 1); } else { System.out.println("The args's number is wrong!"); } } catch (Exception e) { System.err.println("Error: "+e); } } }
自定义分库切分类:
/** * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ import org.apache.commons.lang.ArrayUtils; import org.apache.commons.lang.StringUtils; import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.apache.hadoop.classification.InterfaceAudience; import org.apache.hadoop.classification.InterfaceStability; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Writable; import org.apache.hadoop.mapreduce.*; import org.apache.hadoop.mapreduce.lib.db.*; import java.io.DataInput; import java.io.DataOutput; import java.io.IOException; import java.sql.*; import java.util.ArrayList; import java.util.List; /** * A InputFormat that reads input data from an SQL table with sharding. * <p> * ShardingDBInputFormat emits LongWritables containing the record number as * key and DBWritables as value. * * The SQL query, and input class can be using one of the two * setInput methods. */ @InterfaceAudience.Public @InterfaceStability.Stable public class ShardingDBInputFormat<T extends DBWritable> extends DBInputFormat<T> { private static final Log LOG = LogFactory.getLog(ShardingDBInputFormat.class); protected String dbProductName = "DEFAULT"; /** * A Class that does nothing, implementing DBWritable */ @InterfaceStability.Evolving public static class NullDBWritable implements DBWritable, Writable { public void readFields(DataInput in) throws IOException { } public void readFields(ResultSet arg0) throws SQLException { } public void write(DataOutput out) throws IOException { } public void write(PreparedStatement arg0) throws SQLException { } } /** * A InputSplit that spans a set of rows 自定义 split 在和源码 class DBInputSplit 类进行对比后,在 462行看到 将 jdbcrul添加到 split对象中 */ @InterfaceStability.Evolving public static class ShardingDBInputSplit extends DBInputSplit{ private String jdbcUrl; private long end = 0; private long start = 0; /** * Default Constructor */ public ShardingDBInputSplit() { } /** * Convenience Constructor * @param jdbcUrl the jdbcUrl for this sharding * @param start the index of the first row to select * @param end the index of the last row to select */ public ShardingDBInputSplit(String jdbcUrl,long start, long end) { this.jdbcUrl=jdbcUrl; this.start = start; this.end = end; } /** {@inheritDoc} */ public String[] getLocations() throws IOException { // TODO Add a layer to enable SQL "sharding" and support locality return new String[] {}; } public String getJdbcUrl(){ return jdbcUrl; } /** * @return The index of the first row to select */ public long getStart() { return start; } /** * @return The index of the last row to select */ public long getEnd() { return end; } /** * @return The total row count in this split */ public long getLength() throws IOException { return end - start; } /** {@inheritDoc} */ public void readFields(DataInput input) throws IOException { // 在读取数据时,先得到jdbcUrl的长度 然后读取这个长度下的 jdbcUrl 最后在读取真正的数据 int len=input.readInt(); byte[] bytes=new byte[len]; input.readFully(bytes); jdbcUrl=new String(bytes); start = input.readLong(); end = input.readLong(); } /** {@inheritDoc} */ public void write(DataOutput output) throws IOException { // 在写出数据时,先写出jdbcUrl的长度 ,然后写出 jdbcUrl的值,最后写出要写的内容的开始位置和结束位置 int len=jdbcUrl.length(); output.writeInt(len); output.writeBytes(jdbcUrl); output.writeLong(start); output.writeLong(end); } } protected String conditions; protected Connection connection; protected String tableName; protected String[] fieldNames; protected DBConfiguration dbConf; /** {@inheritDoc} */ public void setConf(Configuration conf) { dbConf = new DBConfiguration(conf); try { this.connection = createConnection(); DatabaseMetaData dbMeta = connection.getMetaData(); this.dbProductName = dbMeta.getDatabaseProductName().toUpperCase(); } catch (Exception ex) { ex.printStackTrace(); throw new RuntimeException(ex); } tableName = dbConf.getInputTableName(); fieldNames = dbConf.getInputFieldNames(); conditions = dbConf.getInputConditions(); } public Configuration getConf() { return dbConf.getConf(); } public DBConfiguration getDBConf() { return dbConf; } public Connection getConnection() { // TODO Remove this code that handles backward compatibility. if (this.connection == null) { this.connection = createConnection(); } return this.connection; } public Connection createConnection() { try { // System.out.println(dbConf.toString()); // Iterator it = dbConf.getConf().iterator(); // while (it.hasNext()) { // System.out.println(it.next()); // } // // System.out.println(dbConf.getConf().get(DBConfiguration.DRIVER_CLASS_PROPERTY)); Connection newConnection = dbConf.getConnection(); newConnection.setAutoCommit(false); newConnection.setTransactionIsolation( Connection.TRANSACTION_SERIALIZABLE); return newConnection; } catch (Exception e) { e.printStackTrace(); throw new RuntimeException(e); } } Connection createConnection(String jdbcUrl){ try{ Class.forName(dbConf.getConf().get(DBConfiguration.DRIVER_CLASS_PROPERTY)); return DriverManager.getConnection(jdbcUrl, dbConf.getConf().get(DBConfiguration.USERNAME_PROPERTY), dbConf.getConf().get(DBConfiguration.PASSWORD_PROPERTY)); }catch(Exception e) { e.printStackTrace(); throw new RuntimeException(e); } } public String getDBProductName() { return dbProductName; } protected RecordReader<LongWritable, T> createDBRecordReader(InputSplit splita, Configuration conf) throws IOException { // 读取每一个切片,读取后将数据存放在 dbConf.getInputClass()类中来接收读入的split的每一行数据 //如果是sharding则对split进行初始化时重新填入sharding jdbcurl if(conf.getBoolean("tableIsSharding",false)) { ShardingDBInputSplit split = (ShardingDBInputSplit) splita; // 重新定义 split DBConfiguration.configureDB(conf, conf.get(DBConfiguration.DRIVER_CLASS_PROPERTY), split.getJdbcUrl(), conf.get(DBConfiguration.USERNAME_PROPERTY), conf.get(DBConfiguration.PASSWORD_PROPERTY)); } @SuppressWarnings("unchecked") DBInputSplit split = (DBInputSplit) splita; Class<T> inputClass = (Class<T>) (dbConf.getInputClass()); // 对应于文件末尾方法 setInput中的 ----> dbConf.setInputClass(inputClass); 这里这个类是CommonRecord类 // 上面是针对源码的修改 增加部分 ,下面这段是贴上的源码 try { // 根据数据库类型不同 进行解析split的内容并将数据 映射到 CommonRecord类 中 // use database product name to determine appropriate record reader. if (dbProductName.startsWith("ORACLE")) { // use Oracle-specific db reader. return new OracleDBRecordReader<T>(split, inputClass, conf, createConnection(), getDBConf(), conditions, fieldNames, tableName); } else if (dbProductName.startsWith("MYSQL")) { // use MySQL-specific db reader. return new MySQLDBRecordReader<T>(split, inputClass, conf, createConnection(), getDBConf(), conditions, fieldNames, tableName); } else { // Generic reader. return new DBRecordReader<T>(split, inputClass, conf, createConnection(), getDBConf(), conditions, fieldNames, tableName); } } catch (SQLException ex) { throw new IOException(ex.getMessage()); } } /** {@inheritDoc} */ public RecordReader<LongWritable, T> createRecordReader(InputSplit split, TaskAttemptContext context) throws IOException, InterruptedException { // if (context.getConfiguration().getBoolean("tableIsSharding", true)) { // return createDBRecordReader((ShardingDBInputSplit) split, context.getConfiguration()); // } else { // return createDBRecordReader((DBInputSplit) split, context.getConfiguration()); // } return createDBRecordReader(split, context.getConfiguration()); } /** * 支持对水平shardingdb 使用sharding数目个mapper分别去拉取shardingdb 中表数据 * 对非sharding表,使用默认行为进行拉取. * **/ public List<InputSplit> getSplits(JobContext job) throws IOException { List<InputSplit> splits = new ArrayList<InputSplit>(); String dbUrlConnProps=job.getConfiguration().get("dbUrlConnProps",""); // tinyInt1isBit=false boolean tableIsSharding=job.getConfiguration().getBoolean("tableIsSharding",false); // true or fasle int maxSplitRowsCount=job.getConfiguration().getInt("maxSplitRowsCount",50000); if(maxSplitRowsCount>50000){ maxSplitRowsCount=50000; } if(tableIsSharding) { // jdbc:mysql://192.168.1.40:3306/mydb[1~64] String dbProcInstances=job.getConfiguration().get("dbProcInstances");// jdbc:mysql://192.168.1.39:3306/mydb[1~64],192.168.1.42:3306/mydb[1~64] String protocol=dbProcInstances.substring(0,dbProcInstances.indexOf("//"))+"//"; // jdbc:mysql:// String tmp=dbProcInstances.replace(protocol,""); String[] instances=tmp.split(","); // 192.168.1.39:3306/mydb[1~64],192.168.1.42:3306/mydb[1~64] Connection connection=null; ResultSet results = null; Statement statement = null; String jdbcUrl=null; for(String instance:instances) { if (instance.contains("/")) { // 192.168.1.39:3306/mydb[1~64] String prefixBegin=instance.substring(0, instance.indexOf("/"))+"/"; // 192.168.1.39:3306/ String shardings=instance.replace(prefixBegin,""); // mydb[1~64] String dbPrefix=shardings.substring(0,shardings.indexOf("[")); // mydb tmp=shardings.substring(shardings.indexOf("[")+1).replace("]",""); // 1~64 if (tmp.contains("~")) { //only support integer range split by ~ int start = Integer.parseInt(tmp.split("~")[0]); // 1 int end = Integer.parseInt(tmp.split("~")[1]); // 64 for (int i = start; i <= end; i++) { jdbcUrl =this.createJdbcUrl(protocol, prefixBegin, dbPrefix, i, dbUrlConnProps); //jdbc:mysql://192.168.1.39:3306/mydb1?tinyInt1isBit=false,0,23520) 最后的这个 0,23520 不是这次代码中用到的 this.addInputSplit(splits,jdbcUrl,maxSplitRowsCount); } } else if (tmp.contains("|")) { //only support integer list split by | String[] shardingNumArray = tmp.split("\\|"); if (ArrayUtils.isNotEmpty(shardingNumArray)) { for (String shardingNumString : shardingNumArray) { int shardingNum = Integer.parseInt(shardingNumString); jdbcUrl =this.createJdbcUrl(protocol, prefixBegin, dbPrefix, shardingNum, dbUrlConnProps); this.addInputSplit(splits,jdbcUrl,maxSplitRowsCount); } } } } } }else{ ResultSet results = null; Statement statement = null; try { statement = connection.createStatement(); results = statement.executeQuery(getCountQuery()); results.next(); long count = results.getLong(1); int chunks = job.getConfiguration().getInt(MRJobConfig.NUM_MAPS, 1); long chunkSize = (count / chunks); results.close(); statement.close(); // Split the rows into n-number of chunks and adjust the last chunk // accordingly for (int i = 0; i < chunks; i++) { DBInputSplit split; if ((i + 1) == chunks) split = new DBInputSplit(i * chunkSize, count); else split = new DBInputSplit(i * chunkSize, (i * chunkSize) + chunkSize); splits.add(split); } connection.commit(); return splits; } catch (SQLException e) { throw new IOException("Got SQLException", e); } finally { try { if (results != null) { results.close(); } } catch (SQLException e1) {} try { if (statement != null) { statement.close(); } } catch (SQLException e1) {} closeConnection(); } } return splits; } /** * 生成sharing db对应的jdbc url * @param protocol * @param prefixBegin * @param dbPrefix * @param shardingNum * @param dbUrlConnProps * @return */ private String createJdbcUrl(String protocol, String prefixBegin, String dbPrefix, int shardingNum, String dbUrlConnProps) { String jdbcUrl=protocol+prefixBegin+dbPrefix+shardingNum; if (StringUtils.isNotBlank(dbUrlConnProps)){ jdbcUrl = jdbcUrl+"?"+dbUrlConnProps; } return jdbcUrl; } /** * 根据指定的sharding db的url,查询数据行数,并根据maxSplitRowsCount切分InputSplit * @param splits * @param jdbcUrl * @param maxSplitRowsCount */ private void addInputSplit(List<InputSplit> splits,String jdbcUrl,int maxSplitRowsCount) { Connection connection=null; ResultSet results = null; Statement statement = null; connection=createConnection(jdbcUrl); long count=0l; try { statement = connection.createStatement(); results = statement.executeQuery(getCountQuery()); results.next(); count = results.getLong(1); }catch(Exception e){ } finally { try { if (results != null) { results.close(); } if (statement != null) { statement.close(); } if (connection != null) { connection.close(); } } catch (SQLException e) { } } if(count>maxSplitRowsCount){ int chunks=(int)(count/maxSplitRowsCount); if(count%maxSplitRowsCount>0){ chunks++; } long chunkSize = maxSplitRowsCount; for (int c = 0; c < chunks; c++) { ShardingDBInputSplit split; if ((c + 1) == chunks) { split = new ShardingDBInputSplit(jdbcUrl, c * chunkSize, count); // 在这里给 ShardingDBInputSplit类赋值 jdbcUrl 和 这个分片的开头和长度 }else { split = new ShardingDBInputSplit(jdbcUrl, c * chunkSize, (c * chunkSize) + chunkSize); } System.out.println("ShardingDBInputSplit:"+jdbcUrl+","+split.getStart()+","+split.getEnd()); splits.add(split); } }else{ ShardingDBInputSplit split=new ShardingDBInputSplit(jdbcUrl,0,count); System.out.println("no ShardingDBInputSplit:"+jdbcUrl+",0,"+count+")"); splits.add(split); } } /** Returns the query for getting the total number of rows, * subclasses can override this for custom behaviour.*/ protected String getCountQuery() { if(dbConf.getInputCountQuery() != null) { return dbConf.getInputCountQuery(); } StringBuilder query = new StringBuilder(); query.append("SELECT COUNT(*) FROM " + tableName); if (conditions != null && conditions.length() > 0) query.append(" WHERE " + conditions); return query.toString(); } /** * Initializes the map-part of the job with the appropriate input settings. * * @param job The map-reduce job * @param inputClass the class object implementing DBWritable, which is the * Java object holding tuple fields. * @param tableName The table to read data from * @param conditions The condition which to select data with, * eg. '(updated > 20070101 AND length > 0)' * @param orderBy the fieldNames in the orderBy clause. * @param fieldNames The field names in the table * @see #setInput(Job, Class, String, String) */ public static void setInput(Job job, Class<? extends DBWritable> inputClass, String tableName, String conditions, String orderBy, String... fieldNames) { job.setInputFormatClass(ShardingDBInputFormat.class); DBConfiguration dbConf = new DBConfiguration(job.getConfiguration()); dbConf.setInputClass(inputClass); dbConf.setInputTableName(tableName); dbConf.setInputFieldNames(fieldNames); dbConf.setInputConditions(conditions); dbConf.setInputOrderBy(orderBy); } /** * Initializes the map-part of the job with the appropriate input settings. * * @param job The map-reduce job * @param inputClass the class object implementing DBWritable, which is the * Java object holding tuple fields. * @param inputQuery the input query to select fields. Example : * "SELECT f1, f2, f3 FROM Mytable ORDER BY f1" * @param inputCountQuery the input query that returns * the number of records in the table. * Example : "SELECT COUNT(f1) FROM Mytable" * @see #setInput(Job, Class, String, String, String, String...) */ public static void setInput(Job job, Class<? extends DBWritable> inputClass, String inputQuery, String inputCountQuery) { job.setInputFormatClass(ShardingDBInputFormat.class); DBConfiguration dbConf = new DBConfiguration(job.getConfiguration()); dbConf.setInputClass(inputClass); dbConf.setInputQuery(inputQuery); dbConf.setInputCountQuery(inputCountQuery); } protected void closeConnection() { try { if (null != this.connection) { this.connection.close(); this.connection = null; } } catch (SQLException sqlE) { LOG.debug("Exception on close", sqlE); } } }
流程图:
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在本节中,我们将详细介绍 Kettle 数据抽取的全量抽取过程,包括新建抽取转换流、输入控件的选择、输出控件的选择、全量抽取的业务表前处理等内容。 1. 新建抽取转换流 在 Kettle 中,新建一个转换流非常简单,只...
标题中的"使用kettle实现多表数据全量抽取"表明我们将通过Kettle来处理多个数据库表的数据,假设这些表在结构上是完全相同的。这可能涉及到企业内部多个业务系统的数据整合,以获取全局视角。 描述中提到的前提是...
标题“chouuqian.rar_抽签_抽签器网页_自定义抽签_随机抽取”揭示了一个关于在线抽签应用的压缩包文件。这个抽签器网页设计用于实现自定义抽签功能,允许用户根据需要添加不同的人名或其他标识符,并且具备随机抽取...