![]() ![]() I am using this command: LOAD DATA INFILE c:/csv/bigCSV.csv IGNORE INTO TABLE table FIELDS TERMINATED BY, LINES TERMINATED BY rn IGNORE 1 LINES. Again this is for sure not a KNIME issue but a huge red flag that something is off with your DB. I am trying to import 300 mg csv file into mySql table. Here’s an example of a successful data export query: mysql> SELECT FROM yourtable INTO OUTFILE '/tmp/out.txt' Query OK, 6 rows affected (0.00 sec) Now the result of the SELECT statement above is saved as out.txt file. What’s the primary key of that table? That alone could explain the issue. You should be able to import or export data using MySQL LOAD DATA and SELECT INTO FILE statements. InnoDB doesn’t cope well with ‘random’ primary keys. execute ( INSERT INTO test VALUES To execute the script. I would rather fix that than use this dangerous crutch. The credentials we need to use are Server Name Database Name and the table we want to connect to. IMHO this is not a solution as 25 rows / second tells me there simply is something wrong with the database. How to import multiple CSV files into multiple SQL Server tables in one go. So before using this node please make sure that the column types of the KNIME columns and the database columns are compatible.Īnd MySQL is known to do weird stuff with coercing data types so they fit. In your case you just need GetFile -> PutDatabaseRecord. However it does not check the column type compatibility. PutDatabaseRecord allows you to put multiple records from one flow file into a database at a time, without requiring the user to convert to SQL (you can use PutSQL for the latter, but it is less efficient). The node does some preliminary checks such as checking that the column order and column names are compatible. Right now I have a symfony/Doctrine app (PHP) that reads these CSV files and imports them into. For example, one is about 33MB and about 65,000 lines. My company gets a set of CSV files full of bank account info each month that I need to import into a database. Most databases do not perform data checks when loading the data into the table which might lead to a corrupt data table. Best practices for importing large CSV files. I would be extremely careful using the loader with MySQL: ![]()
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