After creating an sqlite table with a generated column in it, the type only shows up, if it was specified, and there can be cases when junk gets into the type description as well.
Example:
create table test(
id integer primary key not null,
gen generated always as (id * 2) stored
);
Using pragma table_xinfo(test); afterwards nets the following output:
0|id|INTEGER|1||1|0
1|gen||0||0|3
The type is simply missing from the correct column.
If the column were to be created with:
gen integer generated always as (id * 2) stored
instead, then the type would correctly show up as INTEGER.
Are there any methods that would get the type of a column in a table without having to resort to parsing the table creation code?
Nevermind, as usual, I find the answer right after asking it. According to sqlite documentation:
The datatype and collating sequence of the generated column are determined only by the datatype and COLLATE clause on the column definition. The datatype and collating sequence of the GENERATED ALWAYS AS expression have no affect on the datatype and collating sequence of the column itself.
Which I assume means, that just as in other places, if the datatype is not specified, it is thought of as a blob.
Related
I am looking at migrating a small sqlite3 db to mysql. I know mysql but new to sqlite3 so have been reading about it online. I used pragma table_info(<table_name>) to get info about the table structure.
From the output I could understand columns with data type TEXT, INTEGER but i do not understand datatype BINARY(32). From sqlite3 documentation on the net there is a BINARY collation, but there is no BINARY datatype. So I just want to understand this this BINARY(32) datatype. Thanks.
SQLite is unusual in datatypes (column types). You can store any type of data in any type of columns with the exception of the rowid column or an alias of the rowid column.
see Rowid Tables
rowid is similar to MySQL AUTO INCREMENT BUT beware of differences
In the example below see how the rowid starts from -100, then -99 .....
AUTOINCREMENT on SQLite is only a constraint as such that enforces that a new id is higher than any existing in the table.
So BINARY, BINARY(32), (rumplestistkin even) are valid for the datatype when defining a column.
However, a column will be given a column affinity and governed by the rules :-
If the column type contains INT the the affinity is INTEGER.
If the column type contains CHAR, CLOB or TEXT, then it's affinity is TEXT.
If the column type contains BLOB then it's affinity is BLOB.
If the column type contains REAL FLOA or DOUB then it's affinity is REAL.
Otherwise the affinity is NUMERIC.
As such BINARY(32) is NUMERIC affinity. However, the column type is of little consequence in regards to storing data. The affinity can affect retrieval a little.
In regard to converting the rules mentioned above could be utilised you could also perhaps find the typeof function of use (example of it's use is in the example along with the results). However, neither will necessarily, indicate how the data is subsequently used which could well be a factor that needs consideration.
SQLite's flexibility with column types aids in converting from other relational databases BUT can be a bit of a hindrance when converting from SQLite.
Note this answer is by no means intended to be comprehensive explanation of the conversion from SQLite to MysQL.
See Datatypes in SQLite
Here's an example that shows that any type can be stored in any column (thus any row/col combination can store different types) :-
DROP TABLE IF EXISTS example;
CREATE TABLE IF NOT EXISTS example (
rowid_alias_must_be_unique_integer INTEGER PRIMARY KEY, -- INTEGER PRIMARY KEY makes the column an alias of the rowid
col_text TEXT,
col_integer INTEGER,
col_real REAL,
col_BLOB BLOB,
col_anyother this_is_a_stupid_column_type
);
INSERT INTO example VALUES (-100,'MY TEXT', 340000,34.5678,x'f0f1f2f3f4f5f6f7f8f9fafbfcfdfeff',100);
INSERT INTO example (col_text,col_integer,col_real,col_blob,col_anyother) VALUES
('MY TEXT','MY TEXT','MY TEXT','MY TEXT','MY TEXT'),
(100,100,100,100,100),
(34.5678,34.5678,34.5678,34.5678,34.5678),
(x'f0f1f2f3f4f5f6f7f8f9fafbfcfdfeff',x'f0f1f2f3f4f5f6f7f8f9fafbfcfdfeff',x'f0f1f2f3f4f5f6f7f8f9fafbfcfdfeff',x'f0f1f2f3f4f5f6f7f8f9fafbfcfdfeff',x'f0f1f2f3f4f5f6f7f8f9fafbfcfdfeff')
;
SELECT
*,
rowid,
typeof(rowid_alias_must_be_unique_integer),
typeof(col_text),
typeof(col_integer),
typeof(col_real),
typeof(col_blob),
typeof(col_anyother)
FROM example
;
DROP TABLE IF EXISTS example;
Running the above results in (Note different SQLtools handle blobs in different ways, Navicat was used to run the above) :-
note that the typeof function returns the storage type as opposed to the affinity. However, the affinity can affect the storage type.
e.g. if the affinity is text then with the exception of a blob the value is stored as text. (see 2. in Datatype in SQLite above).
After reading https://sqlite.org/datatype3.html which states
"SQLite does not have a storage class set aside for storing dates
and/or times."
but able to run this
CREATE TABLE User (ID INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT, BORN_ON DATE NULL)
and then see it in "DB Browser for SQL" like this:
I start to wonder if SQLite does support Date type of it is just "faking" the support using other types. And even if so why the DB Browser see it as a Date? Any meta info stored inside the DB?
SQLite does not fake Date with Numerics.
There is no Date data type in SQLite.
In Datatypes In SQLite Version 3 it is explained clearly that:
SQLite uses a more general dynamic type system
Instead of data types there are 5 Storage Classes: NULL, INTEGER, REAL, TEXT and BLOB.
Also:
Any column in an SQLite version 3 database, except an INTEGER PRIMARY
KEY column, may be used to store a value of any storage class.
So when you use Date as the data type of a column in the CREATE TABLE statement you are not restricted to store in it only date-like values. Actually you can store anything in that column.
Tools like "DB Browser for SQLite" and others may offer various data types to select from to define a column when you create the table.
The selection of the data type that you make is not restrictive, but it is rather indicative of what type of data you want to store in a column.
In fact, you can create a table without even declaring the data types of the columns:
CREATE TABLE tablename(col1, col2)
or use fictional data types:
CREATE TABLE tablename(col1 somedatatype, col2 otherdatatype)
and insert values of any data type:
INSERT INTO tablename(col1, col2) VALUES
(1, 'abc'),
('XYZ', '2021-01-06'),
(null, 3.5)
Based on what Colonel Thirty Two suggested (read more on the page) it seems that when you declare a field as Date its affinity will be numeric.
So SQLite "fakes" Date with Numerics.
And even if so why the DB Browser see it as a Date? Any meta info stored inside the DB?
Yes, it simply stores the type name used when the column was created. The linked page calls it "declared type". In this case you get NUMERIC affinity (DATE is even given as one of the examples in 3.1.1) and it behaves like any other column with this affinity:
A column with NUMERIC affinity may contain values using all five storage classes. When text data is inserted into a NUMERIC column, the storage class of the text is converted to INTEGER or REAL (in order of preference) if the text is a well-formed integer or real literal, respectively. If the TEXT value is a well-formed integer literal that is too large to fit in a 64-bit signed integer, it is converted to REAL. For conversions between TEXT and REAL storage classes, only the first 15 significant decimal digits of the number are preserved. If the TEXT value is not a well-formed integer or real literal, then the value is stored as TEXT. For the purposes of this paragraph, hexadecimal integer literals are not considered well-formed and are stored as TEXT. (This is done for historical compatibility with versions of SQLite prior to version 3.8.6 2014-08-15 where hexadecimal integer literals were first introduced into SQLite.) If a floating point value that can be represented exactly as an integer is inserted into a column with NUMERIC affinity, the value is converted into an integer. No attempt is made to convert NULL or BLOB values.
A string might look like a floating-point literal with a decimal point and/or exponent notation but as long as the value can be expressed as an integer, the NUMERIC affinity will convert it into an integer. Hence, the string '3.0e+5' is stored in a column with NUMERIC affinity as the integer 300000, not as the floating point value 300000.0.
So if you insert dates looking like e.g. "2021-01-05" they will be stored as strings. But
you can also insert strings which don't look like dates.
if you insert "20210105" it will be stored as the number 20210105.
You can use CHECK constraints to prevent inserting non-date strings.
See also https://sqlite.org/lang_datefunc.html which says what (string and number) formats date/time functions expect.
Given we have a simple table like
CREATE TABLE A(
amount INTEGER
);
What is the difference between queries
INSERT INTO A VALUES(4);
and
INSERT INTO A VALUES('12');
As seen in schema, amount is an INTEGER column. The first query operates with just that - an integer, but the second one operates with a string '12'. Yet both queries work just fine, the table gets values 4 and 12, and can select or, say, sum them up correctly as two valid Integers:
SELECT sum(amount) AS "Total" FROM A;
correctly yields 16.
So is there a difference between inserting an integer as (4) and inserting it as ('12') into the INTEGER-type column?
SQLite tries to convert your String into an Integer before inserting the value into your table as described in the manual.
The type affinity of a column is the recommended type for data stored in that column. The important idea here is that the type is recommended, not required. Any column can still store any type of data. It is just that some columns, given the choice, will prefer to use one storage class over another.
I have a simple table "tags" containing a key and a value column. The key is always a string, the value can be either string, int64 or a double value.
I do not have any real data at this point to test with. But I'm curious about the index usage of the value column. I've defined the column as TEXT type - is SQLite still able to use the index on the value column when an int64 or double type is bound to the statement?
Here is the test table:
CREATE TABLE "tags" ("key" TEXT,"value" TEXT DEFAULT (null) );
INSERT INTO "tags" VALUES('test','test');
INSERT INTO "tags" VALUES('testint','1');
INSERT INTO "tags" VALUES('testdouble','2.0');
I see additional "Integer" and "Affinity" entries when analyzing the query via:
explain SELECT value FROM tags where key = "testint" and value >= 1
But I do not see any difference in index usage otherwise (e.g. idxgt is always used). But I'd rather like to have a definite answer rather than relying on wrong assumption with the small test data.
The documentation says:
A column with TEXT affinity stores all data using storage classes NULL, TEXT or BLOB. If numerical data is inserted into a column with TEXT affinity it is converted into text form before being stored.
The sort order is well-defined for all types.
Forcing the affinity to be TEXT makes comparisons on this column with numbers behave as if the values were text, but that is probably what you want.
In any case, indexes do not change the behaviour; they work correctly with all types, and apply affinities in exactly the same way as on non-indexed columns.
I have a SQlite3 table that has typeless columns like in this example:
CREATE TABLE foo(
Timestamp INT NOT NULL,
SensorID,
Value,
PRIMARY KEY(Timestamp, SensorID)
);
I have specific reasons not to declare the type of the columns SensorID and Value.
When inserting rows with numeric SensorID and Value columns I notice that they are being written as plain text into the .db file.
When I change the CREATE TABLE statement to...
CREATE TABLE foo(
Timestamp INT NOT NULL,
SensorID INT,
Value REAL,
PRIMARY KEY(Timestamp, SensorID)
);
...then the values seem to be written in some binary format to the .db file.
Since I need to write several millions of rows to the database, I have concerns about the file size this data produces and so would like to avoid value storage in plain text form.
Can I force SQLite to use binary representation in it's database file without using explicitly typed columns?
Note: Rows are currently written with PHP::PDO using prepared statements.
The example in section 3.4 in the sqlite docs about types demonstrates the insertion of a number as int in a column without an explicit declaration of type. I guess the trick is leaving out the quotes around the number, which would convert it to a string (which, in the case of typed columns, would be coerced back into a number).
Section 2 in the page linked above also provides a lot of info about the type conversions taking place.