For the given English description, write an SQL command such that it accomplishes every step. An SQL query works by selecting data from a table where certain conditions apply. A table contains columns where every row in that table must have a value for each column. Every table has a primary key that uniquely identifies each row, usually an id. To choose which columns are returned you specify that after the "SELECT" statement. Next, you use a "FROM" statement to specify what tables you want to select the data from. When you specify a table you can rename it with the "AS" statement. You can reference that table by whatever name follows the "AS" statement. If you want to select data from multiple tables you need to use the "JOIN" statement. This will join the tables together by pairing a row in one table with every row in the other table (Cartesian Product). To limit the number of rows returned you should use the "ON" statement. This will only return rows where the condition specified after the statement is true, this is usually an equals operator with primary keys. You can also use the "WHERE" statement to specify that only rows with column values statisfying a certain condition, should be returned. The "GROUP BY" statement will group rows together that have equal column values for whatever columns follows the statement. The "HAVING" statement will return groups that statisfy whatever condition follows the statement. Any column(s) being returned from grouped rows must either be an aggregate function, (AVG, MAX, COUNT, SUM, ...) of a column, or the column(s) that the data was grouped by. To sort the returned data you can use the "ORDER BY" command which will order the data by whatever aggregate function or column follows the statement. The "DESC" statement will sort in descending order and the "ASC" statement will sort in ascending order. Finally, you can use the "LIMIT" statement to return a certain number of rows. When "*" is used in an SQL statement every column is returned. For example, SELECT * FROM table WHERE attribute = 1, will select every column from rows with the attribute column equal to 1.

[Q]: Did M0 direct , write , executive produce , edit , and produce M1 , M2 , and M3
[A]: SELECT count(*) WHERE {
M0 ns:film.director.film M1 .
M0 ns:film.director.film M2 .
M0 ns:film.director.film M3 .
M0 ns:film.editor.film M1 .
M0 ns:film.editor.film M2 .
M0 ns:film.editor.film M3 .
M0 ns:film.producer.films_executive_produced M1 .
M0 ns:film.producer.films_executive_produced M2 .
M0 ns:film.producer.films_executive_produced M3 .
M0 ns:film.producer.film|ns:film.production_company.films M1 .
M0 ns:film.producer.film|ns:film.production_company.films M2 .
M0 ns:film.producer.film|ns:film.production_company.films M3 .
M0 ns:film.writer.film M1 .
M0 ns:film.writer.film M2 .
M0 ns:film.writer.film M3
}


[Q]: Did M2 influence a German costume designer
[A]: SELECT count(*) WHERE {
?x0 a ns:film.film_costumer_designer .
?x0 ns:people.person.nationality ns:m.0345h .
M2 ns:influence.influence_node.influenced ?x0
}


[Q]: Did M0 influence M1 , M2 , and M3 , marry M5 , M6 , and M7 , and influence M4
[A]:
SELECT count(*) WHERE {
FILTER ( M0 != M5 ) .
FILTER ( M0 != M6 ) .
FILTER ( M0 != M7 ) .
M0 ns:influence.influence_node.influenced M1 .
M0 ns:influence.influence_node.influenced M2 .
M0 ns:influence.influence_node.influenced M3 .
M0 ns:influence.influence_node.influenced M4 .
M0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M5 .
M0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M6 .
M0 ns:people.person.spouse_s/ns:people.marriage.spouse|ns:fictional_universe.fictional_character.married_to/ns:fictional_universe.marriage_of_fictional_characters.spouses M7
}