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I have a file that can contain from 3 to 4 columns of numerical values which are separated by comma. Empty fields are defined with the exception when they are at the end of the row:
1,2,3,4,5
1,2,3,,5
1,2,3
The following table was created in MySQL:
+-------+--------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------+------+-----+---------+-------+
| one | int(1) | YES | | NULL | |
| two | int(1) | YES | | NULL | |
| three | int(1) | YES | | NULL | |
| four | int(1) | YES | | NULL | |
| five | int(1) | YES | | NULL | |
+-------+--------+------+-----+---------+-------+
I am trying to load the data using MySQL LOAD command:
LOAD DATA INFILE '/tmp/testdata.txt' INTO TABLE moo FIELDS
TERMINATED BY "," LINES TERMINATED BY "\n";
The resulting table:
+------+------+-------+------+------+
| one | two | three | four | five |
+------+------+-------+------+------+
| 1 | 2 | 3 | 4 | 5 |
| 1 | 2 | 3 | 0 | 5 |
| 1 | 2 | 3 | NULL | NULL |
+------+------+-------+------+------+
The problem lies with the fact that when a field is empty in the raw data and is not defined, MySQL for some reason does not use the columns default value (which is NULL) and uses zero. NULL is used correctly when the field is missing alltogether.
Unfortunately, I have to be able to distinguish between NULL and 0 at this stage so any help would be appreciated.
Thanks
The output of SHOW WARNINGS:
+---------+------+--------------------------------------------------------+
| Level | Code | Message |
+---------+------+--------------------------------------------------------+
| Warning | 1366 | Incorrect integer value: '' for column 'four' at row 2 |
| Warning | 1261 | Row 3 doesn't contain data for all columns |
| Warning | 1261 | Row 3 doesn't contain data for all columns |
+---------+------+--------------------------------------------------------+
–
This will do what you want. It reads the fourth field into a local variable, and then sets the actual field value to NULL, if the local variable ends up containing an empty string:
LOAD DATA INFILE '/tmp/testdata.txt'
INTO TABLE moo
FIELDS TERMINATED BY ","
LINES TERMINATED BY "\n"
(one, two, three, @vfour, five)
SET four = NULLIF(@vfour,'')
If they're all possibly empty, then you'd read them all into variables and have multiple SET statements, like this:
LOAD DATA INFILE '/tmp/testdata.txt'
INTO TABLE moo
FIELDS TERMINATED BY ","
LINES TERMINATED BY "\n"
(@vone, @vtwo, @vthree, @vfour, @vfive)
one = NULLIF(@vone,''),
two = NULLIF(@vtwo,''),
three = NULLIF(@vthree,''),
four = NULLIF(@vfour,'')
–
–
–
When reading data with LOAD DATA
INFILE, empty or missing columns are
updated with ''. If you want a NULL
value in a column, you should use \N
in the data file. The literal word
“NULL” may also be used under some
circumstances.
So you need to replace the blanks with \N like this:
1,2,3,4,5
1,2,3,\N,5
1,2,3
–
–
–
The behaviour is different depending upon the database configuration. In the strict mode this would throw an error else a warning.
Following query may be used for identifying the database configuration.
mysql> show variables like 'sql_mode';
–
Preprocess your input CSV to replace blank entries with \N.
Attempt at a regex: s/,,/,\n,/g and s/,$/,\N/g
Good luck.
–
–
–
Show variables like "`secure_file_priv`";
Note: keep your csv file in location given by the above command.
create table assessments (course_code varchar(5),batch_code varchar(7),id_assessment int, assessment_type varchar(10), date int , weight int);
Note: here the 'date' column has some blank values in the csv file.
LOAD DATA INFILE 'C:/ProgramData/MySQL/MySQL Server 8.0/Uploads/assessments.csv'
INTO TABLE assessments
FIELDS TERMINATED BY ','
OPTIONALLY ENCLOSED BY ''
LINES TERMINATED BY '\n'
IGNORE 1 ROWS
(course_code,batch_code,id_assessment,assessment_type,@date,weight)
SET date = IF(@date = '', NULL, @date);
Converted the input file to include \N for the blank column data using the below sed command in UNix terminal:
sed -i 's/,,/,\\N,/g' $file_name
and then use LOAD DATA INFILE command to load to mysql
You can firstly read the file in pandas as pandas dataframe and then wherever you want the values to be NULL , there you can replace the empty values with string 'NULL' using replace function (dataframe_name.replace(value_to_be_replaced,'NULL') and save the new dataframe in .csv foramt using to_csv function.
After this when you will import the csv file into MySQL using :
Connect to the server with local-infile system variable :
mysql --local-infile=1 -u root -p
When you are inside MySQL server on cmd, set the global variables by using this command:
SET GLOBAL local_infile=1;
Use your Database and load the file into the table:
Load the file
load data local infile '<path_to_file>' into table <table_name>
columns terminated by "," optionally enclosed by "'" ignore 1 lines.
Then all the NULL values in the dataset will be recognised as NULL only.
I hope it helps.
MySQL converts empty fields into empty string '', hence why the error when inserting numerical fields, since the conversion from string to INT is not a thing. Even when the INT field in the create table is DEFAULT NULL.
The straightforward solution would be to preprocess the csv and insert \N (not \n) as NULL fields.
This can be done quickly with:
sed -i 's/,,/,\\N,/g file.csv'
sed -i 's/,,/,\\N,/g file.csv'
It is important to do it twice because consecutive blank fields will be skipped, since the second separator of a blank field is also the first separator of the next field, and it will be skipped after the first substitution.
In other words, if you use only one command, something,,,,SomethingElse will be converted to something,\N,,\N,SomethingElse.
Maybe there is a smarter way to do it with a more advanced command but this works just fine. You can loop through all csvs in a dir and run the command twice for each file.
(reference)
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