Python Data Persistence – Table with Compound Partition Key
In the above example, the products table had been defined to have a partition key with a single primary key. Rows in such a table are stored in different nodes depending upon the hash value of the primary key. However, data is stored across the cluster using a slightly different method when the table has a compound primary key. The following table’s primary key comprises two columns.
cq1sh:mykeyspace> create table products             . . . (             . . . productID int,             . . . manufacturer text,             . . . name text,             . . . price int,             . . . primary key(manufacturer, productID)             . . . ) ;
For this table, ‘manufacturer’ is the partition key and ‘productID’ behaves as a cluster key. As a result products with similar ‘manufacturer’ are stored in the same node. Let us understand with the help of the following example. The table contains the following data.
Example
cq1sh:mykeyspace> select * from products; productid    |  manufacturer |  name      |    price ---------------+-----------------+----------------+-----------     5      |  'Epson'      | 'Printer'     |  9000     10      |  'IBall'        |  'Keyboard'  |   1000     1      |  'Acer'       | 'Laptop'     |  25000      8      |  'Acer'       |  'Tab'       |  10000     2      |  'Samsung'   |  'TV'        |  40000     4      |  'Epson'      |  'Scanner'   |   5000     7      |  'IBall'       |  'Mouse'    |   500     6      |  'Samsung'   |  'Mobile'    |  15000     9      |  'Samsung'   |  'AC'       |  35000     3      |  ’IBall'       |  'Router'    |  2000  (10 rows)
Rows in the above table will be stored among nodes such that products from the same manufacturer are together, (figure 12.5)
