I am having multiple values which are encoded to byte arrays and stored in a BLOB column of mysql
encode(val1)+encode(val2)+encode(val3)
Now, I have to do LIKE operation on the BLOB column with encode(val1).
How to do this operation and how does it work internally?
Related
I've been trying to figure this out for two days now and would really appreciate some help. I've imported data from a csv where one field contained html data encoded in base64.
The idea is to loop over every row and run FROM_BASE64 on it.
How do I structure a query that:
Loops over all lines
Calls FRON_BASE64 for each line
Runs UPDATE (or similar functionality) on that same row and column
Context: I'm running MariaDB (MySQL equivalent).
Thanks for any help!
Typically base64 would be used for binary data. You probably shouldn't store the decoded data in the same column as the base64-coded string. If necessary you should ALTER TABLE to add a new column that is VARBINARY or BLOB type, to hold the binary data.
ALTER TABLE MyTable ADD COLUMN BinaryField BLOB;
You can then fill that column with an UPDATE statement:
UPDATE MyTable SET BinaryField = FROM_BASE64(EncodedField);
I'm using a BLOB data type to store big array of bytes. Arrays are produced and consumed by C# application, but now I need to edit my BLOB in SQL language.
The question is:
How can I update just one byte in a BLOB field using SQL?
I want to save very long text like base64(image) encoded string into mysql table.
in this case, is it slow to execute query(select, insert, update, delete)?
select * from A where index = x
table A
column index
column base64String <-- MEDIUMTEXT type
No not at all, depends on how you are fetching the data not on the size or type of the data. IF you store only the file name of the image file and fetch image from a path might be faster because you can cache those files. But When you store file in base64 encoded please use blob data type in mysql.
I dont have any performance issue with storing file in base64, I am using blob as a mysql datatype for the image encoded data. Slow and faster again depends on your complexity of your query and depends on consumer that how your DB consumer gonna consume the data. There are different mechanism for optimization for consuming data from DB but as soon as I store my user's profile image on DB I use Blob as a data type.
I have matlab data table T in my matlab with more than 40,000 rows. I want to insert this table into MySQL database. This table T has columns with different data types(char, date, integer). I tried following:
fastinsert(conn,'tablename',colnames2,T)
I even tried with "Insert" and datainsert". I converted table to cellarray, but still it didn't work. Then I tried to convert that cellarray into mat, but i couldn't convert it to matrix It says all the content should be of same data type to convert it into matrix.
Is there any way i can insert my data table present in matlab to MySQL database?
Instead of converting your data from a cell array to a matrix have you tried converting it to a table using cell2table() and then using insert(). There is an example in the MATLAB documentation that can be found here.
The linked example uses multiple data types in a cell and then converts them to a table (instead of a matrix) which can then be written to the database with mixed data types.
I'd like to know if you can query a blob (large/medium any kind) column and retrieve the bytes from N to M so you can query a huge blob file and only get small chunks of it in your resultset. If this is possible in MySQL, how can you do it (an example please!)?
I found this question for plain text but what about doing the same for bytes?
You can find the answer right here: MySQL blob: how to get just a subset of the stored data
MySQL treats blobs the same as strings (more or less):
BLOB values are treated as binary strings (byte strings). They have no character set, and sorting and comparison are based on the numeric values of the bytes in column values.
So all the usual string functions work on blobs. In particular, you can use substring to grab just part of of a blob.
That said, storing a multi-gigabyte data file in a relational database as a BLOB isn't the best thing to do. You'd be better off storing the file's metadata in the database and leaving the file itself in the file system; file systems are pretty good at managing files, relational databases are good at handling structured data.