![]() We can also run INSERT statements like so: INSERT INTO arctype (column, column_2) VALUES ('Demo', 'Demo 2') 'Demo Data' inserts a row with the text 'Demo Data' inside a column column_1.Īfter we would run such a SQL statement, some demo data will be added to our table.VALUES specifies that values will be set after this parameter.column_1 refers to the column name of the column to which we want to insert data.demo_table is the name of the table into which we want to insert the data.The INSERT INTO statement tells MySQL we want to INSERT data instead of SELECTing, deleting, or updating it.INSERT INTO demo_table (column_1) VALUES ('Demo Data') Īs you can see, the statement is comprised of a few parts: In its most basic form, the statement looks like so: To begin with, the INSERT statement, as its name suggests allows us to insert data into a table. However, when we are facing those two choices, we probably are not sure which one of them is better – that's what we are looking into today. ![]() Such a statement might be helpful if we find ourselves working with a lot of data inside our database instances. However, MySQL also has another way that dumps can be imported – LOAD DATA INFILE. ![]() One of those – the INSERT INTO statement – could be considered a standard way to do so. This would be a great advancement of this product.If you have been working with MySQL for a while, you probably already know that MySQL offers multiple methods for importing data. I am concerned about loading a file to any 3rd party (even if it is only processed by local javascript - I can't tell, my js isn't that good). Not advocating for them but it is the same idea and just may save some of us a bit of time. I have found a website recently that does just this (can't tell you as first post hehe) but check out SSIS give you the option to choose how many rows to test this way, but it only takes one row to stuff up your layout. I have written the layout discovery code in the past it traverses the whole file and refines the field attribute as it goes (staring with specifics, refining to more general). You are given sample data file and then end up refining your table layout. The typical scenario is loading a new data set as a one-off or starting a new ETL. ![]() I've been coding SQL for over 20 years and this "problem" is fairly common but not well solved, even by the likes of SQL Server Integration Services. I have CSV files with lot of fields and I import a few lines with phpmyadmin (it createst the table) and import the rest of the lines with HeidiSQL.not the best solution. This doesn't seem like it would be that difficult to do, programmatically, which makes it even more surprising that it hasn't already been done.
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