导入失败，报错：“too many filtered rows xxx, “ErrorURL“:“

最新推荐文章于 2025-03-31 13:54:51 发布

jerry-89

最新推荐文章于 2025-03-31 13:54:51 发布

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分类专栏： DorisDB 文章标签：数据库

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文章讲述了在使用DataX从MySQL导入数据到ApacheDoris时遇到的错误，主要原因是CSV文件列数少于表结构定义。提供了调整DataX配置和修改CSV格式的解决办法，包括更改line_delimiter和column_separator以避免导入错误。

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一、问题：

注：前面能正常写入，突然就报错，导入失败，报错：“too many filtered rows xxx, "ErrorURL":"

{"TxnId":769494,"Label":"datax_doris_writer_bf176078-15d7-414f-8923-b0eb5f6d5da1","TwoPhaseCommit":"false","Status":"Fail","Message":"[INTERNAL_ERROR]too many filtered rows","NumberTotalRows":325476,"NumberLoadedRows":325473,"NumberFilteredRows":3,"NumberUnselectedRows":0,"LoadBytes":94697450,"LoadTimeMs":1498,"BeginTxnTimeMs":0,"StreamLoadPutTimeMs":2,"ReadDataTimeMs":117,"WriteDataTimeMs":1495,"CommitAndPublishTimeMs":0,"ErrorURL":"http://IP:8040/api/_load_error_log?file=__shard_8/error_log_insert_stmt_ce466641e5bad2af-99171040d6f76fb8_ce466641e5bad2af_99171040d6f76fb8"}
http://IP:8040/api/_load_error_log?file=__shard_8/error_log_insert_stmt_ce466641e5bad2af-99171040d6f76fb8_ce466641e5bad2af_99171040d6f76fb8"

内容如下：
Reason: actual column number in csv file is  less than  schema column number.actual number: 11, column separator: [	], line delimiter: [
], schema column number: 16; . src line [320746671400	6540dbac03e56b6315de10f8	279ca466-2047-42f5-9932-1730703644e4	10	沙河市中瑞玻璃制品有限公司玻璃深加工生产线扩建项...	2023-10-31 00:00:00	130582	10	1004	10	]; 
Reason: actual column number in csv file is  less than  schema column number.actual number: 1, column separator: [	], line delimiter: [
], schema column number: 16; . src line [2023-10-31]; 
Reason: actual column number in csv file is  less than  schema column number.actual number: 6, column separator: [	], line delimiter: [
], schema column number: 16; . src line [	\N	0	1698749356710	2023-10-31 18:49:16	2023-11-13 11:05:48];

二、解决办法

Datax 代码库编译

从datax 代码库拉取代码，执行编译

git clone https://github.com/alibaba/DataX.git
cd datax
mvn package assembly:assembly -Dmaven.test.skip=true

注：MYSQL版本改成你使用的版本；

more pom.xml

编译完成后可以在 datax/target/Datax 下看到datax.tar.gz 包

my_import.json

{
    "job": {
        "content": [
            {
                "reader": {
                    "name": "mysqlreader",
                    "parameter": {
                        "column": ["id","order_code","line_code","remark","unit_no","unit_name","price"],
                        "connection": [
                            {
                                "jdbcUrl": ["jdbc:mysql://localhost:3306/demo"],
                                "table": ["employees_1"]
                            }
                        ],
                        "username": "root",
                        "password": "xxxxx",
                        "where": ""
                    }
                },
                "writer": {
                    "name": "doriswriter",
                    "parameter": {
                        "loadUrl": ["127.0.0.1:8030"],
                        "loadProps": {
                        },
                        "column": ["id","order_code","line_code","remark","unit_no","unit_name","price"],
                        "username": "root",
                        "password": "xxxxxx",
                        "postSql": ["select count(1) from all_employees_info"],
                        "preSql": [],
                        "flushInterval":30000,
                        "connection": [
                          {
                            "jdbcUrl": "jdbc:mysql://127.0.0.1:9030/demo",
                            "selectedDatabase": "demo",
                            "table": ["all_employees_info"]
                          }
                        ],
                        "loadProps": {
                            "format": "json",
                            "strip_outer_array":"true",
                            "line_delimiter": "\\x02"
                        }
                    }
                }
            }
        ],
        "setting": {
            "speed": {
                "channel": "1"
            }
        }
    }
}

备注：
"loadProps": {
  "format": "json",
  "strip_outer_array":"true",
  "line_delimiter": "\\x02"
}
这里我们使用了 JSON 格式导入数据
line_delimiter 默认是换行符，可能会和数据中的值冲突，我们可以使用一些特殊字符或者不可见字符，避免导入错误
strip_outer_array ：在一批导入数据中表示多行数据，Doris 在解析时会将数组展开，然后依次解析其中的每一个 Object 作为一行数据
更多 Stream load 参数请参照 [Stream load文档](Stream load - Apache Doris)
如果是 CSV 格式我们可以这样使用
"loadProps": {
   "format": "csv",
   "column_separator": "\\x01",
   "line_delimiter": "\\x02"
}
CSV 格式要特别注意行列分隔符，避免和数据中的特殊字符冲突，这里建议使用隐藏字符，默认列分隔符是：\t，行分隔符：\n