列式存储格式之parquet读写

概述

Apache Parquet是Hadoop生态系统中任何项目均可使用的列式存储格式，更高压缩比以及更小IO操作。网上许多写入parquet需要在本地安装haddop环境，下面介绍一种不需要安装haddop即可写入parquet文件的方式，以及通过两种方式来读取parquet文件。下面开始入坑了...

parquet写入

1.pom依赖

 
     org.apache.avro
     avro
     1.8.2
 
 
     org.apache.hadoop
     hadoop-core
     1.2.1
 
 
     org.apache.parquet
     parquet-hadoop
     1.8.1
 
 
 
     org.apache.parquet
     parquet-avro
     1.8.1
 

2.定义schema（实体类）

package com.kestrel;

public class User {
    private String id;
    private String name;
    private String password;

    public User() {
    }

    public User(String id, String name, String password) {
        this.id = id;
        this.name = name;
        this.password = password;
    }

    public String getId() {
        return id;
    }



    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public String getPassword() {
        return password;
    }

    public void setPassword(String password) {
        this.password = password;
    }

    @Override
    public String toString() {
        return "User{" +
                "id='" + id + '\'' +
                ", name='" + name + '\'' +
                ", password='" + password + '\'' +
                '}';
    }
}

1. AvroParquetWriter 写入

   List users = new ArrayList<>();
   
   User user1 = new User("1","huangchixin","123123");
   User user2 = new User("2","huangchixin2","123445");
   users.add(user1);
   users.add(user2);
   Path dataFile = new Path("./tmp/demo.snappy.parquet");
   
   // Write as Parquet file.
   try (ParquetWriter writer = AvroParquetWriter.builder(dataFile)
        .withSchema(ReflectData.AllowNull.get().getSchema(User.class))
        .withDataModel(ReflectData.get())
        .withConf(new Configuration())
        .withCompressionCodec(SNAPPY)
        .withWriteMode(OVERWRITE)
        .build()) {
   
       for (User user : users) {
           writer.write(user);
       }
   }

   parquet读取

   1. AvroParquetReader读取，需要指定对象实例，或者也可自定义json 字符串

   // Read from Parquet file.
   try (ParquetReader reader = AvroParquetReader.builder(dataFile)
       .withDataModel(new ReflectData(User.class.getClassLoader()))
       .disableCompatibility()
       .withConf(new Configuration())
       .build()) {
       User user;
   
       while ((user = reader.read()) != null) {
       System.out.println(user);
       }
   }

   1. ParquetFileReader读取，不需要

      • 列实体

      package com.kestrel;
      
      /**
       * @Auther: 12640
       * @Date: 2021/1/1 15:13
       * @Description:
       */
      public class TableHead {
      
          /**
           * 列名
           */
          private String name;
          /**
           * 存储 列的 数据类型
           */
          private String type;
          /**
           * 所在列
           */
          private Integer index;
          public String getType() {
              return type;
          }
      
          public void setType(String type) {
              this.type = type;
          }
      
          public String getName() {
              return name;
          }
      
          public void setName(String name) {
              this.name = name;
          }
      
          public Integer getIndex() {
              return index;
          }
      
          public void setIndex(Integer index) {
              this.index = index;
          }
      }
      

      • parquet 实体类

      package com.kestrel;
      
      import java.util.List;
      
      /**
       * @Auther: 12640
       * @Date: 2021/1/1 15:14
       * @Description:
       */
      public class TableResult {
          /**
           * 解析文件的表头信息 暂时只对 arrow，csv 文件有效
           */
          private List< TableHead> columns;
          /**
           * 数据内容
           */
          private List data;
      
          public List< TableHead> getColumns() {
              return columns;
          }
      
          public void setColumns(List< TableHead> columns) {
              this.columns = columns;
          }
      
          public List getData() {
              return data;
          }
      
          public void setData(List data) {
              this.data = data;
          }
      }
      

      • 读取parquet文件

      import com.fasterxml.jackson.databind.ObjectMapper;
      import com.google.common.collect.Lists;
      import org.apache.hadoop.conf.Configuration;
      import org.apache.hadoop.fs.Path;
      import org.apache.parquet.column.page.PageReadStore;
      import org.apache.parquet.example.data.Group;
      import org.apache.parquet.example.data.simple.convert.GroupRecordConverter;
      import org.apache.parquet.format.converter.ParquetMetadataConverter;
      import org.apache.parquet.hadoop.ParquetFileReader;
      import org.apache.parquet.hadoop.ParquetReader;
      import org.apache.parquet.hadoop.example.GroupReadSupport;
      import org.apache.parquet.hadoop.metadata.ParquetMetadata;
      import org.apache.parquet.io.ColumnIOFactory;
      import org.apache.parquet.io.MessageColumnIO;
      import org.apache.parquet.io.RecordReader;
      import org.apache.parquet.schema.GroupType;
      import org.apache.parquet.schema.MessageType;
      import org.apache.parquet.schema.OriginalType;
      import org.apache.parquet.schema.Type;
      
      import java.io.File;
      import java.io.IOException;
      import java.util.ArrayList;
      import java.util.List;
      
      public class ReadParquet {
      
      
          public static void main(String[] args) throws Exception {
      
              TableResult tableResult = parquetReaderV2(new File("./tmp/demo.snappy.parquet"));
              ObjectMapper mapper = new ObjectMapper();
              String jsonString = mapper.writerWithDefaultPrettyPrinter()
                      .writeValueAsString(tableResult);
              System.out.println(jsonString);
          }
      
      
          public static TableResult parquetReaderV2(File file) throws Exception {
              long start = System.currentTimeMillis();
              haddopEnv();
              Path path = new Path(file.getAbsolutePath());
      
              Configuration conf = new Configuration();
              TableResult table = new TableResult();
      
              //二位数据列表
              List> dataList = Lists.newArrayList();
      
              ParquetMetadata readFooter = ParquetFileReader.readFooter(conf, path, ParquetMetadataConverter.NO_FILTER);
      
              MessageType schema = readFooter.getFileMetaData().getSchema();
              ParquetFileReader r = new ParquetFileReader(conf, readFooter.getFileMetaData(), path, readFooter.getBlocks(), schema.getColumns());
      //        1.9.0使用以下创建对象
      //        ParquetFileReader r = new ParquetFileReader(conf, path, readFooter);
      
              PageReadStore pages = null;
              try {
                  while (null != (pages = r.readNextRowGroup())) {
                      final long rows = pages.getRowCount();
      //                logger.info(file.getName()+" 行数: " + rows);
      
                      final MessageColumnIO columnIO = new ColumnIOFactory().getColumnIO(schema);
                      final RecordReader recordReader = columnIO.getRecordReader(pages,
                              new GroupRecordConverter(schema));
                      for (int i = 0; i <= rows; i++) {
      //                    System.out.println(recordReader.shouldSkipCurrentRecord());
                          final Group g = recordReader.read();
                          if (i == 0) {
                              // 设置表头列名
                              table.setColumns(parquetColumn(g));
                              i++;
                          }
                          // 获取行数据
                          List