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SQL tutorial

This tutorial is a demonstration of the SQL feature introduced in Tarantool 2.x series. There are two ways to go through this tutorial:

  • read what we say the results are and take our word for it, or
  • copy and paste each section and see everything work with Tarantool 2.4.

You will encounter all the functionality that you’d encounter in an «SQL-101» course.

Requests will be done using Tarantool as a client. Start Tarantool and, optionally, enter the Tarantool configuration request, for example:

tarantool> box.cfg{}

Before Tarantool 2.0 you needed to say box.cfg{...} prior to performing any database operations. Now you can start working with the database outright. Tarantool initiates the database module and applies default settings.

A feature of the client console program is that you can switch languages and specify the end-of-statement delimiter.

Here we say: default language is SQL and statements end with semicolons.

tarantool> \set language sql
tarantool> \set delimiter ;

Start with simple SQL statements just to be sure they’re there.

CREATE TABLE table1 (column1 INTEGER PRIMARY KEY, column2 VARCHAR(100));
INSERT INTO table1 VALUES (1, 'A');
UPDATE table1 SET column2 = 'B';
SELECT * FROM table1 WHERE column1 = 1;

The result of the SELECT statement will look like this:

tarantool> SELECT * FROM table1 WHERE column1 = 1;
- - [1, 'B']

Reality check: actually the result will include include initial fields called «metadata», the names and data types of each column. For all SELECT examples we show only the result rows without showing the metadata.

Here is CREATE TABLE with more details:

  • There are multiple columns, with different data types.
  • There is a PRIMARY KEY (unique and not-null) for two of the columns.
CREATE TABLE table2 (column1 INTEGER,
                     column2 VARCHAR(100),
                     column3 SCALAR,
                     column4 DOUBLE,
                     PRIMARY KEY (column1, column2));

The result will be: «row_count: 1» (no error).

Try to put 5 rows in the table:

  • The INTEGER and DOUBLE columns get numbers.
  • The VARCHAR and SCALAR columns get strings (the SCALAR strings are expressed as hexadecimals).
INSERT INTO table2 VALUES (1, 'AB', X'4142', 5.5);
INSERT INTO table2 VALUES (1, 'CD', X'2020', 1E4);
INSERT INTO table2 VALUES (1, 'AB', X'A5', -5.5);
INSERT INTO table2 VALUES (2, 'AB', X'2020', 12.34567);
INSERT INTO table2 VALUES (-1000, '', X'', 0.0);

Получим следующий результат:

  • The third INSERT will fail because of a primary-key violation (1, 'AB' is a duplication).
  • The other four INSERT statements will succeed.

Retrieve the 4 rows in the table, in descending order by column2, then (where the column2 values are the same) in ascending order by column4.

«*» is short for «all columns».

SELECT * FROM table2 ORDER BY column2 DESC, column4 ASC;

Получим следующий результат:

- - [1, 'CD', '  ', 10000]
  - [1, 'AB', 'AB', 5.5]
  - [2, 'AB', '  ', 12.34567]
  - [-1000, '', '', 0]

Retrieve some of what you inserted:

  • The first statement uses the LIKE comparison operator which is asking for «first character must be „A“, the next characters can be anything.»
  • The second statement uses logical operators and parentheses, so the ANDed expressions must be true, or the ORed expression must be true. Notice the columns don’t have to be indexed.
SELECT column1, column2, column1 * column4 FROM table2 WHERE column2
LIKE 'A%';
SELECT column1, column2, column3, column4 FROM table2
    WHERE (column1 < 2 AND column4 < 10)
    OR column3 = X'2020';

The results will be:

- - [1, 'AB', 5.5]
  - [2, 'AB', 24.69134]


- - [-1000, '', '', 0]
  - [1, 'AB', 'AB', 5.5]
  - [1, 'CD', '  ', 10000]
  - [2, 'AB', '  ', 12.34567]

Retrieve with grouping.

The rows which have the same values for column2 are grouped and are aggregated – summed, counted, averaged – for column4.

SELECT column2, SUM(column4), COUNT(column4), AVG(column4)
FROM table2
GROUP BY column2;

Получим следующий результат:

- - ['', 0, 1, 0]
  - ['AB', 17.84567, 2, 8.922835]
  - ['CD', 10000, 1, 10000]

Insert more rows, containing NULL values.

NULL is not the same as Lua nil; it commonly is used in SQL for unknown or not-applicable.

INSERT INTO table2 VALUES (1, NULL, X'4142', 5.5);
INSERT INTO table2 VALUES (0, '!!@', NULL, NULL);
INSERT INTO table2 VALUES (0, '!!!', X'00', NULL);

Получим следующий результат:

  • The first INSERT will fail because NULL is not permitted for a column that was defined with a PRIMARY KEY clause.
  • The other INSERT statements will succeed.

Make a new index on column4.

There already is an index for the primary key. Indexes are useful for making queries faster. In this case, the index also acts as a constraint, because it prevents two rows from having the same values in column4. However, it is not an error that column4 has multiple occurrences of NULLs.

CREATE UNIQUE INDEX i ON table2 (column4);

The result will be: «rowcount: 1» (no error).

Make a table which will have some of the columns of table2, and some of the rows of table2.

You can do this by combining INSERT with SELECT. Then select everything in the resultant subset table.

CREATE TABLE table3 (column1 INTEGER, column2 VARCHAR(100), PRIMARY KEY
INSERT INTO table3 SELECT column1, column2 FROM table2 WHERE column1 <> 2;
SELECT * FROM table3;

Получим следующий результат:

- - [-1000, '']
  - [0, '!!!']
  - [0, '!!@']
  - [1, 'AB']
  - [1, 'CD']

A subquery is a query within a query.

Here we find all the rows in table2 whose (column1, column2) values are not in table3.

SELECT * FROM table2 WHERE (column1, column2) NOT IN (SELECT column1,
column2 FROM table3);

The result is, unsurprisingly, the single row which we deliberately excluded when we inserted the rows in the INSERT ... SELECT statement:

- - [2, 'AB', '  ', 12.34567]

A join is a combination of two tables. There is more than one way to do them in Tarantool: «Cartesian joins», «left outer joins», etc.

Here we’re just showing the most typical case, where column values from one table match column values from another table.

SELECT * FROM table2, table3
    WHERE table2.column1 = table3.column1 AND table2.column2 = table3.column2
    ORDER BY table2.column4;

Получим следующий результат:

- - [0, '!!!', "\0", null, 0, '!!!']
  - [0, '!!@', null, null, 0, '!!@']
  - [-1000, '', '', 0, -1000, '']
  - [1, 'AB', 'AB', 5.5, 1, 'AB']
  - [1, 'CD', ' ', 10000, 1, 'CD']

First we make a table which includes a «constraint» that there must not be any rows containing 13 in column2. Then we try to insert such a row.

(column2 <> 13));
INSERT INTO table4 VALUES (12, 13);

Result: the insert fails, as it should, with the message «'Check constraint failed ''ck_unnamed_TABLE4_1'': column2 <> 13'».

First we make a table which includes a «constraint» that there must not be any rows containing values that do not appear in table2.

When we made table2, we specified that its «primary key» columns were (column1, column2).

CREATE TABLE table5 (column1 INTEGER, column2 VARCHAR(100),
    PRIMARY KEY (column1),
    FOREIGN KEY (column1, column2) REFERENCES table2 (column1, column2));


  • The first INSERT statement succeeds because table3 contains a row with [2, 'AB', ' ', 12.34567].
  • The second INSERT statement, correctly, fails with the message «Failed to execute SQL statement: FOREIGN KEY constraint failed».

Due to earlier INSERT statements, these values are in table2 column4: {0, NULL, NULL, 5.5, 10000, 12.34567}. We will add 5 to every one of them except the one with 0. (Adding 5 to NULL will result in NULL, as SQL arithmetic requires.) Then we’ll use SELECT to see what happened to column4.

UPDATE table2 SET column4 = column4 + 5 WHERE column4 <> 0;
SELECT column4 FROM table2 ORDER BY column4;

The result is: {NULL, NULL, 0, 10.5, 17.34567, 10005}.

Due to earlier INSERT statements, there are now 6 rows in table2:

- - [-1000, '', '', 0]
  - [0, '!!!', "\0", null]
  - [0, '!!@', null, null]
  - [1, 'AB', 'AB', 10.5]
  - [1, 'CD', '  ', 10005]
  - [2, 'AB', '  ', 17.34567]

We will try to delete the last and first of these rows.

DELETE FROM table2 WHERE column1 = 2;
DELETE FROM table2 WHERE column1 = -1000;
SELECT COUNT(column1) FROM table2;

Получим следующий результат:

  • The first DELETE statement causes an error message because (remember?) there’s a foreign-key constraint.
  • The second DELETE statement succeeds.
  • The SELECT statement shows that there are now only 5 rows remaining.

Now we want to make another «constraint», that there must not be any rows in table1 containing values that do not appear in table5. We couldn’t do this when we created table1 because at that time table5 did not exist. But we can add constraints to existing tables with the ALTER TABLE statement.

    FOREIGN KEY (column1) REFERENCES table5 (column1);
    FOREIGN KEY (column1) REFERENCES table5 (column1);

Result: the ALTER TABLE statement fails the first time because there is a row in table1, and ADD CONSTRAINT requires that the table be empty. But after we delete that row, the ALTER TABLE statement succeeds the second time. Thus we have set up a chain of references, from table1 to table5 and from table5 to table2.

The idea of a trigger is: if a change (INSERT or UPDATE or DELETE) happens, then a further action – perhaps another INSERT or UPDATE or DELETE – will happen.

There are many variants, the one we’ll illustrate here is: just after doing an update in table3, do an update in table2. We will specify this as FOR EACH ROW, so (since there are 5 rows in table3) the trigger will be activated 5 times.

SELECT column4 FROM table2 WHERE column1 = 2;
BEGIN UPDATE table2 SET column4 = column4 + 1 WHERE column1 = 2; END;
UPDATE table3 SET column2 = column2;
SELECT column4 FROM table2 WHERE column1 = 2;


  • The first SELECT shows that the original value of column4 in table2 where column1 = 2 was: 17.34567.

  • The second SELECT returns:

    - - [22.34567]

You can manipulate string data (usually defined with CHAR or VARCHAR data types) in many ways.

We’ll illustrate here:

  • the || operator for concatenation and
  • the SUBSTR function for extraction.
SELECT column2, column2 || column2, SUBSTR(column2, 2, 1) FROM table2;

Получим следующий результат:

- - ['!!!', '!!!!!!', '!']
  - ['!!@', '!!@!!@', '!']
  - ['AB', 'ABAB', 'B']
  - ['CD', 'CDCD', 'D']
  - ['AB', 'ABAB', 'B']

You can also manipulate number data (usually defined with INTEGER or DOUBLE data types) in many ways.

We’ll illustrate here:

  • the << operator for shift left and
  • the % operator for modulo.
SELECT column1, column1 << 1, column1 << 2, column1 % 2 FROM table2;

Получим следующий результат:

- - [0, 0, 0, 0]
  - [0, 0, 0, 0]
  - [1, 2, 4, 1]
  - [1, 2, 4, 1]
  - [2, 4, 8, 0]

Tarantool can handle:

  • integers anywhere in the 4-byte integer range,
  • approximate-numerics anywhere in the 8-byte IEEE floating point range,
  • any Unicode characters, with UTF-8 encoding and a choice of collations.

Here we will insert some such values in a new table, and see what happens when we select them, with arithmetic on a number column and ordering by a string column.

CREATE TABLE t6 (column1 INTEGER, column2 VARCHAR(10), column4 DOUBLE,
PRIMARY KEY (column1));
INSERT INTO t6 VALUES (-1234567890, 'АБВГД', 123456.123456);
INSERT INTO t6 VALUES (+1234567890, 'GD', 1e30);
INSERT INTO t6 VALUES (10, 'FADEW?', 0.000001);
SELECT column1 + 1, column2, column4 * 2 FROM t6 ORDER BY column2;

The result is:

- - [6, 'ABCDEFG', null]
  - [11, 'FADEW?', 2e-06]
  - [1234567891, 'GD', 2e+30]
  - [-1234567889, 'АБВГД', 246912.246912]

A view, or «viewed table», is virtual, that is, its rows aren’t physically in the database, their values are calculated from other tables.

Here we’ll create a view v3 based on table3, then we select from it.

CREATE VIEW v3 AS SELECT SUBSTR(column2,1,2), column4 FROM t6 WHERE
column4 >= 0;

The result is:

- - ['АБ', 123456.123456]
  - ['FA', 1e-06]
  - ['GD', 1e+30]

By putting WITH + SELECT in front of a SELECT, we can make a sort of temporary view that lasts for the duration of the statement.

Here we’ll select from the sort of temporary view.

WITH cte AS (
             SELECT SUBSTR(column2,1,2), column4 FROM t6 WHERE column4
             >= 0)

Result: the same as the result we got with CREATE VIEW earlier:

- - ['АБ', 123456.123456]
  - ['FA', 1e-06]
  - ['GD', 1e+30]

Tarantool can handle statements like SELECT 55; (select without FROM) like some other popular DBMSs. But it also handles the more standard statement VALUES (expression [, expression ...]);.

Here we’ll use both styles.

SELECT 55 * 55, 'The rain in Spain';
VALUES (55 * 55, 'The rain in Spain');

The result of either statement will be:

- - [3025, 'The rain in Spain']

What database objects have we created? We can find out about:

  • tables with SELECT * FROM "_space";
  • indexes with SELECT * FROM "_index";
  • triggers with SELECT * FROM "_trigger"; (These names will be familiar to old Tarantool users because we’re actually selecting from NoSQL «system spaces».)

Here we will select from _space.

SELECT "id", "name", "owner", "engine" FROM "_space" WHERE "name"='TABLE3';

The result is (we know we will get a row because we created table3 earlier):

- - [517, 'TABLE3', 1, 'memtx']

Now we will change the settings so that the console accepts statements written in Lua instead of statements written in SQL. (More ways to switch languages will exist in Tarantool clients in our next version.)

This doesn’t mean we have left the SQL world though, because we can invoke SQL statements using a Lua function: box.execute(string).

Here we’ll switch languages, and ask to select again what’s in table3. These statements must be entered separately.

tarantool> \set language lua
tarantool> box.execute([[SELECT * FROM table3;]]);

Showing both the statements and the results:

tarantool> \set language lua
tarantool> box.execute([[SELECT * FROM table3;]]);
- - [-1000, '']
  - [0, '!!!']
  - [0, '!!@']
  - [1, 'AB']
  - [1, 'CD']

We’ve illustrated a lot of SQL, but does it scale? To answer that, let’s make a bigger table.

For this we are going to use Lua. We will not explain the Lua, because that’s in the Lua section of the Tarantool manual. Just copy-and-paste these instructions and wait for about a minute.

box.execute("CREATE TABLE tester (s1 INT PRIMARY KEY, s2 VARCHAR(10))");

function string_function()
   local random_number
   local random_string
   random_string = ""
   for x = 1,10,1 do
     random_number = math.random(65, 90)
     random_string = random_string .. string.char(random_number)
   return random_string

function main_function()
   local string_value, t, sql_statement
   for i = 1,1000000,1 do
     string_value = string_function()
     sql_statement = "INSERT INTO tester VALUES (" .. i .. ",'" .. string_value .. "')"
start_time = os.clock();
end_time = os.clock();
'insert done in ' .. end_time - start_time .. ' seconds';

The result is: you now have a table with a million rows, with a message saying «insert done in 88.570578 seconds».

Now that we have something a bit larger to play with, let’s see how long it takes to SELECT.

The first query we’ll do will automatically go via an index, because s1 is the primary key.

The second query we’ll do will not go via an index, because for s2 we didn’t say CREATE INDEX xxxx ON tester (s2);.

box.execute([[SELECT * FROM tester WHERE s1 = 73446;]]);
box.execute([[SELECT * FROM tester WHERE s2 LIKE 'QFML%';]]);

The result is:

  • the first statement will finish instantaneously,
  • the second statement will be noticeably slower but still a fraction of a second.

We’re done. We’ve shown that Tarantool 2.x has a very reasonable subset of SQL, and it works.

The rest of these commands will simply destroy all the database objects that were created so that you can do the demonstration again. These statements must be entered separately.

tarantool> \set language sql
tarantool> DROP TABLE tester;
tarantool> DROP TABLE table1;
tarantool> DROP VIEW v3;
tarantool> DROP TRIGGER tr;
tarantool> DROP TABLE table5;
tarantool> DROP TABLE table4;
tarantool> DROP TABLE table3;
tarantool> DROP TABLE table2;
tarantool> DROP TABLE t6;
tarantool> \set language lua
tarantool> os.exit();
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