Question: I would like to make this process in batches, because of the volume. 

Here's my code:

```
 getconn = conexiones()
 con = getconn.mysqlDWconnect()
 with con:
     cur = con.cursor(mdb.cursors.DictCursor)
     cur.execute("SELECT id, date, product_id, sales FROM sales")
     rows = cur.fetchall()

```

How can I implement an index to fetch the data in batches?

Answer: 
First point: a python `db-api.cursor` is an iterator, so unless you really **need** to load a whole batch in memory at once, you can just start with using this feature, ie instead of:

```
cursor.execute("SELECT * FROM mytable")
rows = cursor.fetchall()
for row in rows:
   do_something_with(row)

```

you could just:

```
cursor.execute("SELECT * FROM mytable")
for row in cursor:
   do_something_with(row)

```

Then if your db connector's implementation still doesn't make proper use of this feature, it will be time to add LIMIT and OFFSET to the mix:

```
# py2 / py3 compat
try:
    # xrange is defined in py2 only
    xrange
except NameError:
    # py3 range is actually p2 xrange
    xrange = range

cursor.execute("SELECT count(*) FROM mytable")
count = cursor.fetchone()[0]
batch_size = 42 # whatever

for offset in xrange(0, count, batch_size):
    cursor.execute(
        "SELECT * FROM mytable LIMIT %s OFFSET %s", 
        (batch_size, offset))
   for row in cursor:
       do_something_with(row)

```
You can use 

```
SELECT id, date, product_id, sales FROM sales LIMIT X OFFSET Y;

```

where X is the size of the batch you need and Y is current offset (X times number of current iterations for example)