Twp-download: command not found

根据提供的引用内容，Twp-download不是Docker的命令，因此可能是由于拼写错误或未安装所致。请尝试使用正确的命令或安装所需的软件包。如果您确定该命令存在于某个软件包中，请尝试使用以下命令在CentOS上安装该软件包：

sudo yum install <package-name>

请将<package-name>替换为您要安装的软件包名称。如果您不确定软件包的名称，请查看软件包的官方文档或使用以下命令搜索软件包：

sudo yum search <keyword>

请将<keyword>替换为您要搜索的关键字。

相关问题

String sql = "SELECT id, data_cal_date, stock_block_code, stock_block_name, " + "SUM(block_ref_compact_bal) AS block_ref_compact_bal " + "FROM (" + " SELECT UUID() AS id, '" + lastTD + "' AS data_cal_date, " + " biv.stock_block_code, " + " biv.stock_block_name, " + " ztd.lend_rate * ztd.lend_num * twp.close_price / SUM(ztd.lend_num * twp.close_price) AS block_ref_compact_bal " + " FROM bid_info_view biv " + " LEFT JOIN zrq_trade_detail ztd ON biv.ts_code = ztd.ts_code " + " LEFT JOIN temp_wind_price twp ON biv.ts_code = twp.ts_code " + " GROUP BY biv.stock_block_code, biv.stock_block_name" + ") t " + "GROUP BY id, data_cal_date, stock_block_code, stock_block_name"; tEnv.executeSql(sql).print(); 其中一个ts_code 存在多个lend_rate，报错Expression 'ztd.lend_rate' is not being grouped

在你提供的代码中，报错是由于你在SELECT子句中引用了一个未在GROUP BY子句中进行分组的列 ztd.lend_rate。Flink SQL要求在SELECT子句中引用的列必须要么进行聚合，要么在GROUP BY子句中进行分组。

为了解决这个问题，你可以在GROUP BY子句中添加 ztd.lend_rate 列，或者将其包装在聚合函数中。以下是修改后的代码示例：

String sql = "SELECT id, data_cal_date, stock_block_code, stock_block_name, " +
        "SUM(block_ref_compact_bal) AS block_ref_compact_bal " +
        "FROM (" +
        "    SELECT UUID() AS id, '" + lastTD + "' AS data_cal_date, " +
        "        biv.stock_block_code, " +
        "        biv.stock_block_name, " +
        "        SUM(ztd.lend_rate * ztd.lend_num * twp.close_price) / SUM(ztd.lend_num * twp.close_price) AS block_ref_compact_bal " +
        "    FROM bid_info_view biv " +
        "    LEFT JOIN zrq_trade_detail ztd ON biv.ts_code = ztd.ts_code " +
        "    LEFT JOIN temp_wind_price twp ON biv.ts_code = twp.ts_code " +
        "    GROUP BY biv.stock_block_code, biv.stock_block_name, ztd.lend_rate" +
        ") t " +
        "GROUP BY id, data_cal_date, stock_block_code, stock_block_name";

tEnv.executeSql(sql).print();

在这个修改后的代码中，我们将 ztd.lend_rate 列添加到了 GROUP BY 子句中，以满足 Flink SQL 的要求。或者，你也可以使用 SUM 聚合函数来对 ztd.lend_rate 进行聚合，这样就不需要将其添加到 GROUP BY 子句中。

请确保根据你的业务需求选择适当的解决方案。

String sql = "select id,data_cal_date,stock_block_code,stock_block_name,block_ref_compact_bal from(" + "SELECT UUID() as id,'" + lastTD + "' as data_cal_date," + "biv.stock_block_code," + "biv.stock_block_name," + "sum (ztd.lend_rate * ztd.lend_num * twp.close_price / sum(ztd.lend_num * twp.close_price)) as block_ref_compact_bal " + "from bid_info_view biv " + "left join zrq_trade_detail ztd on " + "biv.ts_code = ztd.ts_code " + "left join temp_wind_price twp " + "on biv.ts_code = twp.ts_code " + "group by biv.stock_block_code,biv.stock_block_name " + ")"; tEnv.executeSql(sql).print(); 报错SQL validation failed. From line 1, column 178 to line 1, column 267: Aggregate expressions cannot be nested

在你提供的代码中，报错是由于在聚合函数中嵌套了另一个聚合函数导致的。在 Flink SQL 中，聚合函数不能嵌套使用。

具体来说，你使用了两个聚合函数：`SUM(ztd.lend_rate * ztd.lend_num * twp.close_price)` 和 `SUM(ztd.lend_num * twp.close_price)`。这是不允许的。

为了解决这个问题，你可以将第一个聚合函数的计算结果提取为一个子查询，然后在外部查询中使用该结果进行计算。以下是修改后的代码示例：

String sql = "SELECT id, data_cal_date, stock_block_code, stock_block_name, " +
        "SUM(block_ref_compact_bal) AS block_ref_compact_bal " +
        "FROM (" +
        "    SELECT UUID() AS id, '" + lastTD + "' AS data_cal_date, " +
        "        biv.stock_block_code, " +
        "        biv.stock_block_name, " +
        "        ztd.lend_rate * ztd.lend_num * twp.close_price / SUM(ztd.lend_num * twp.close_price) AS block_ref_compact_bal " +
        "    FROM bid_info_view biv " +
        "    LEFT JOIN zrq_trade_detail ztd ON biv.ts_code = ztd.ts_code " +
        "    LEFT JOIN temp_wind_price twp ON biv.ts_code = twp.ts_code " +
        "    GROUP BY biv.stock_block_code, biv.stock_block_name" +
        ") t " +
        "GROUP BY id, data_cal_date, stock_block_code, stock_block_name";

tEnv.executeSql(sql).print();

在这个修改后的代码中，我们将第一个聚合函数的计算结果提取为子查询，并在外部查询中进行了第二个聚合函数的计算。这样就避免了聚合函数嵌套的问题。

请注意，如果你的 Flink 版本较低，可能不支持将聚合函数用于聚合结果的情况。在这种情况下，你可能需要将聚合函数的计算逻辑拆分为多个步骤，在中间步骤使用临时表或视图来保存部分结果。