I am a beginner with databases and I am not sure to understand them properly.
As far as I understand given a table with several columns I can make queries like: SELECT * FROM table WHERE col1>3
.
This query has complexity N
. In order to make the search more efficient I can use col1
as index. In this case the same query should have complexity log(N)
.
Now as far as I understood a column is made searchable in sqlalchemy setting it as a primary key.
If this is correct I do not understand why I am not able to set columns with duplicates as primary key.
For example:
import sqlite3
from sqlalchemy import *
metadata = MetaData()
table = Table('example', metadata,
Column('col1', Integer, primary_key=True),
Column('col2', Integer))
engine = create_engine('sqlite:///:memory:', echo=True)
con = engine.connect()
table.create(engine, checkfirst=True)
data = [{'col1':1, 'col2':2}, {'col1':3, 'col2':4}, {'col1':3, 'col2':4}]
ins = table.insert().values(data)
con.execute(ins)
print list(con.execute("SELECT * FROM example"))
returns
IntegrityError: (sqlite3.IntegrityError) PRIMARY KEY must be unique [SQL: u'INSERT INTO example (col1, col2) VALUES (?, ?), (?, ?), (?, ?)'] [parameters: (1, 2, 3, 4, 3, 4)]
How can I make a non unique column searchable in log(N)?
EDIT: The example is written using sqlite but I am actually working with postgres .
Now as far as I understood a column is made searchable in sqlalchemy setting it as a primary key.
A primary key column is automatically indexed, but you frequently need to index non-unique columns. You'd do this with the index
keyword argument :
table = Table('example', metadata,
Column('col1', Integer, index=True),
Column('col2', Integer)
)
You can see in the log file the corresponding SQL:
INFO sqlalchemy.engine.base.Engine CREATE INDEX ix_example_col1 ON example (col1)
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