使用fastjson读取超巨json文件引起的GC问题

项目中需要将巨量数据生成的json文件解析,并写入数据库,使用了 alibaba 的 fastjson,在实践过程中遇到了 GC 问题,记录如下:

数据大约为70万条,文件大小在3~4G左右,使用 fastjson 官方推荐的 Stream Api 例3 的示例,在读取到30万数据时,内存使用量开始迅速上升,CPU也迅速达到百分之百,在读取到40万数据左右时,出现 GC。

代码如下:

import com.alibaba.fastjson.JSONObject;
import com.alibaba.fastjson.JSONReader;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.jdbc.core.namedparam.NamedParameterJdbcTemplate;
import org.springframework.jdbc.core.namedparam.SqlParameterSourceUtils;
import org.springframework.stereotype.Component;
import java.io.*;
import java.util.*;

@Component
@Slf4j
public class EnterDatabaseUtils {
    @Autowired
    private NamedParameterJdbcTemplate namedParameterJdbcTemplate;

    private final int batchTotal = 50000;


    public boolean enterData(String databaseName, String tableName, File file, String[] fields) {
        String fileName = file.getName();
        try {
            JSONReader reader = new JSONReader(new InputStreamReader(new FileInputStream(file.getAbsoluteFile()),"UTF-8"));
            String insertSql = "INSERT INTO `" + databaseName  + "`.`" + tableName  + "`"
                            + " (`" + StringUtils.join(fields, "`,`") + "`)"
                            + " VALUES(:" + StringUtils.join(fields, ",:") + ")";
            long count = 1;
            ArrayList<Map<String, Object>> recordList = new ArrayList<>();
            reader.startArray();
            while (reader.hasNext()) {
                reader.startObject();
                JSONObject = reader.readObject(JSONObject.class);
                if (count <= batchTotal) {
                    recordList.add(record);
                    count ++;
                }
                if (batchTotal + 1 == count) {
                    namedParameterJdbcTemplate.batchUpdate(insertSql, SqlParameterSourceUtils.createBatch(recordList));
                    count = 1;
                    recordList.clear();
                }
            }
            if (recordList.size() > 0) {
                namedParameterJdbcTemplate.batchUpdate(insertSql, SqlParameterSourceUtils.createBatch(recordList));
                recordList.clear();
            }
            reader.endArray();
            reader.close();
            return true;
        } catch (Exception e) {
            log.error(databaseName + "." + tableName + ":插入失败");
            log.error("", e);
            return false;
        }
    }
}

测试代码:

import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;
import java.io.File;

@RunWith(SpringRunner.class)
@SpringBootTest
public class EnterDatabaseUtilsTest {

    @Autowired
    private EnterDatabaseUtils enterDatabaseUtils;

    @Test
    public void testEnterDatabase() {
        File file = new File("/xxx/xxx/xxx.json");
        String[] fields = {........};
        boolean res = enterDatabaseUtils.enterData("xxxx", "xxxx", file, );
    }

}

开始的时候,怀疑是 namedParameterJdbcTemplate 引起的内存占用疯涨。但是将所有的数据库相关操作删除,仅保留json读取代码,内存仍然疯涨并导致 GC。

遂怀疑是 fastjson 使用不当,阅读了大量文章之后,终于在 Json少量数据解析 一文中找到了答案:单行直接 readObject 会导致内存不断被消耗!

将代码改为使用 startObject 将每行中的 key、value 单独解析,内存和CPU占用稳定无增长,问题解决。

改进后的代码如下:

import com.alibaba.fastjson.JSONObject;
import com.alibaba.fastjson.JSONReader;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.jdbc.core.namedparam.NamedParameterJdbcTemplate;
import org.springframework.jdbc.core.namedparam.SqlParameterSourceUtils;
import org.springframework.stereotype.Component;
import java.io.*;
import java.util.*;

@Component
@Slf4j
public class EnterDatabaseUtils {
    @Autowired
    private NamedParameterJdbcTemplate namedParameterJdbcTemplate;

    private final int batchTotal = 50000;


    public boolean enterData(String databaseName, String tableName, File file, String[] fields) {
        String fileName = file.getName();
        try {
            JSONReader reader = new JSONReader(new InputStreamReader(new FileInputStream(file.getAbsoluteFile()),"UTF-8"));
            String insertSql = "INSERT INTO `" + databaseName  + "`.`" + tableName  + "`"
                            + " (`" + StringUtils.join(fields, "`,`") + "`)"
                            + " VALUES(:" + StringUtils.join(fields, ",:") + ")";
            long count = 1;
            ArrayList<Map<String, Object>> recordList = new ArrayList<>();
            Map<String, Object> record = new HashMap<>();
            reader.startArray();
            while (reader.hasNext()) {
                reader.startObject();
                while (reader.hasNext()) {
                    record.put(reader.readString(), reader.readObject());
                }
                reader.endObject();
                if (count <= batchTotal) {
                    recordList.add(record);
                    count ++;
                }
                if (batchTotal + 1 == count) {
                    namedParameterJdbcTemplate.batchUpdate(insertSql, SqlParameterSourceUtils.createBatch(recordList));
                    count = 1;
                    recordList.clear();
                }
            }
            if (recordList.size() > 0) {
                namedParameterJdbcTemplate.batchUpdate(insertSql, SqlParameterSourceUtils.createBatch(recordList));
                recordList.clear();
            }
            reader.endArray();
            reader.close();
            return true;
        } catch (Exception e) {
            log.error(databaseName + "." + tableName + ":插入失败");
            log.error("", e);
            return false;
        }
    }
}

 

posted on 2019-06-27 21:10  刘兴伟  阅读(4519)  评论(0编辑  收藏  举报

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