import java.io.BufferedReader; import java.io.File; import java.io.FileReader; import java.io.IOException; import java.util.Random; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.log4j.Logger; import org.apache.parquet.example.data.Group; import org.apache.parquet.example.data.GroupFactory; import org.apache.parquet.example.data.simple.SimpleGroupFactory; import org.apache.parquet.hadoop.ParquetReader; import org.apache.parquet.hadoop.ParquetReader.Builder; import org.apache.parquet.hadoop.ParquetWriter; import org.apache.parquet.hadoop.example.GroupReadSupport; import org.apache.parquet.hadoop.example.GroupWriteSupport; import org.apache.parquet.schema.MessageType; import org.apache.parquet.schema.MessageTypeParser; public class ReadParquet { static Logger logger=Logger.getLogger(ReadParquet.class); public static void main(String[] args) throws Exception { // parquetWriter("test\\parquet-out2","input.txt"); parquetReaderV2("test\\parquet-out2"); } static void parquetReaderV2(String inPath) throws Exception{ GroupReadSupport readSupport = new GroupReadSupport(); Builder<Group> reader= ParquetReader.builder(readSupport, new Path(inPath)); ParquetReader<Group> build=reader.build(); Group line=null; while((line=build.read())!=null){ System.out.println(line.toString()); } System.out.println("读取结束"); } //新版本中new ParquetReader()所有构造方法好像都弃用了,用上面的builder去构造对象 static void parquetReader(String inPath) throws Exception{ GroupReadSupport readSupport = new GroupReadSupport(); ParquetReader<Group> reader = new ParquetReader<Group>(new Path(inPath),readSupport); Group line=null; while((line=reader.read())!=null){ System.out.println(line.toString()); } System.out.println("读取结束"); } /** * * @param outPath 输出Parquet格式 * @param inPath 输入普通文本文件 * @throws IOException */ static void parquetWriter(String outPath,String inPath) throws IOException{ MessageType schema = MessageTypeParser.parseMessageType("message Pair {\n" + " required binary city (UTF8);\n" + " required binary ip (UTF8);\n" + " repeated group time {\n"+ " required int32 ttl;\n"+ " required binary ttl2;\n"+ "}\n"+ "}"); GroupFactory factory = new SimpleGroupFactory(schema); Path path = new Path(outPath); Configuration configuration = new Configuration(); GroupWriteSupport writeSupport = new GroupWriteSupport(); writeSupport.setSchema(schema,configuration); ParquetWriter<Group> writer = new ParquetWriter<Group>(path,configuration,writeSupport); //把本地文件读取进去,用来生成parquet格式文件 BufferedReader br =new BufferedReader(new FileReader(new File(inPath))); String line=""; Random r=new Random(); while((line=br.readLine())!=null){ String[] strs=line.split("\\s+"); if(strs.length==2) { Group group = factory.newGroup() .append("city",strs[0]) .append("ip",strs[1]); Group tmpG =group.addGroup("time"); tmpG.append("ttl", r.nextInt(9)+1); tmpG.append("ttl2", r.nextInt(9)+"_a"); writer.write(group); } } System.out.println("write end"); writer.close(); } }
说下schema(写Parquet格式数据需要schema,读取的话"自动识别"了schema)
/* * 每一个字段有三个属性:重复数、数据类型和字段名,重复数可以是以下三种: * required(出现1次) * repeated(出现0次或多次) * optional(出现0次或1次) * 每一个字段的数据类型可以分成两种: * group(复杂类型) * primitive(基本类型) * 数据类型有 * INT64, INT32, BOOLEAN, BINARY, FLOAT, DOUBLE, INT96, FIXED_LEN_BYTE_ARRAY */ maven依赖(我用的1.7)
<dependency> <groupId>org.apache.parquet</groupId> <artifactId>parquet-hadoop</artifactId> <version>1.7.0</version> </dependency>
时间: 2024-10-29 19:09:48