WITH Clause
A WITH clause defines one or more named common table expressions (CTEs). Each CTE encapsulates a result set that can be referenced by another CTE in the same WITH clause, or by the primary query of the WITH clause. Vertica can execute the CTE on each reference (inline expansion), or materialize the result set as a temporary table that it reuses for all references. In both cases, WITH clauses can help simplify complicated queries and avoid statement repetition.
Syntax
WITH [ /*+ENABLE_WITH_CLAUSE_MATERIALIZATION */ ] {
cte‑identifier [ ( column-aliases ) ] AS (
[ subordinate-WITH-clause ]
query-expression )
} [,…]
Parameters
| /*+ENABLE_WITH_CLAUSE_MATERIALIZATION*/ | Enables materialization of all queries in the current WITH clause. Otherwise, materialization is set by configuration parameter WithClauseMaterialization, by default set to 0 (disabled). If WithClauseMaterialization is disabled, materialization is automatically cleared when the primary query of the WITH clause returns. For details, see Materialization of WITH Clause. |
| cte‑identifier |
Identifies a common table expression (CTE) within a WITH clause. This identifier is available to CTEs of the same WITH clause, and of parent and child WITH clauses (if any). CTE identifiers of the outermost (primary) WITH clause are also available to the primary query. All CTE identifiers of the same WITH clause must be unique. For example, the following WITH clause defines two CTEs, so they require unique identifiers: WITH -- query sale amounts for each region regional_sales AS (SELECT … ), top_regions AS ( SELECT … ) ) |
| column-aliases |
A comma-delimited list of result set column aliases. These aliases map to column expressions in the CTE query. If omitted, result set columns can only be referenced by the names used in the query. In the following example, CTE
WITH revenue ( vkey, total_revenue ) AS (
SELECT vendor_key, SUM(total_order_cost)
FROM store.store_orders_fact
GROUP BY vendor_key ORDER BY 1)
SELECT v.vendor_name, v.vendor_address, v.vendor_city, r.total_revenue
FROM vendor_dimension v JOIN revenue r ON v.vendor_key = r.
|
| subordinate‑WITH‑clause |
A WITH clause that is nested within the current one. CTEs of this WITH clause can only reference CTEs of the same clause, and of parent and child WITH clauses. The primary query can only reference CTEs in the primary (outermost) WITH clause. It cannot reference the CTEs of any nested WITH clause. |
| query-expression | The query of a given CTE. |
Restrictions
- A WITH query cannot refer to its own output.
- WITH clauses only support SELECT and INSERT statements. They do not support UPDATE, or DELETE statements.
Examples
Single WITH clause with single CTE
The following SQL defines a WITH clause with one CTE, revenue, which aggregates data in table store.store_orders_fact. The primary query references the WITH clause result set twice: in its JOIN clause and predicate:
-- define WITH clause
WITH revenue ( vkey, total_revenue ) AS (
SELECT vendor_key, SUM(total_order_cost)
FROM store.store_orders_fact
GROUP BY vendor_key ORDER BY 1)
-- End WITH clause
-- primary query
SELECT v.vendor_name, v.vendor_address, v.vendor_city, r.total_revenue
FROM vendor_dimension v JOIN revenue r ON v.vendor_key = r.vkey
WHERE r.total_revenue = (SELECT MAX(total_revenue) FROM revenue )
ORDER BY vendor_name;
vendor_name | vendor_address | vendor_city | total_revenue
------------------+----------------+-------------+---------------
Frozen Suppliers | 471 Mission St | Peoria | 49877044
(1 row)
Single WITH clause and multiple CTEs
In the following example, the WITH clause contains two CTEs:
regional_salestotals sales for each regiontop_regionsuses the result set fromregional_salesto identify the three regions with the highest sales:
The primary query aggregates sales by region and departments in the top_regions result set:
WITH
-- query sale amounts for each region
regional_sales (region, total_sales) AS (
SELECT sd.store_region, SUM(of.total_order_cost) AS total_sales
FROM store.store_dimension sd JOIN store.store_orders_fact of ON sd.store_key = of.store_key
GROUP BY store_region ),
-- query previous result set
top_regions AS (
SELECT region, total_sales
FROM regional_sales ORDER BY total_sales DESC LIMIT 3
)
-- primary query
-- aggregate sales in top_regions result set
SELECT sd.store_region AS region, pd.department_description AS department, SUM(of.total_order_cost) AS product_sales
FROM store.store_orders_fact of
JOIN store.store_dimension sd ON sd.store_key = of.store_key
JOIN public.product_dimension pd ON of.product_key = pd.product_key
WHERE sd.store_region IN (SELECT region FROM top_regions)
GROUP BY ROLLUP (region, department) ORDER BY region, product_sales DESC, GROUPING_ID();
region | department | product_sales
---------+----------------------------------+---------------
East | | 1716917786
East | Meat | 189837962
East | Produce | 170607880
East | Photography | 162271618
East | Frozen Goods | 141077867
East | Gifts | 137604397
East | Bakery | 136497842
East | Liquor | 130410463
East | Canned Goods | 128683257
East | Cleaning supplies | 118996326
East | Dairy | 118866901
East | Seafood | 109986665
East | Medical | 100404891
East | Pharmacy | 71671717
MidWest | | 1287550770
MidWest | Meat | 141446607
MidWest | Produce | 125156100
MidWest | Photography | 122666753
MidWest | Frozen Goods | 105893534
MidWest | Gifts | 103088595
MidWest | Bakery | 102844467
MidWest | Canned Goods | 97647270
MidWest | Liquor | 97306898
MidWest | Cleaning supplies | 90775242
MidWest | Dairy | 89065443
MidWest | Seafood | 82541528
MidWest | Medical | 76674814
MidWest | Pharmacy | 52443519
West | | 2159765937
West | Meat | 235841506
West | Produce | 215277204
West | Photography | 205949467
West | Frozen Goods | 178311593
West | Bakery | 172824555
West | Gifts | 172134780
West | Liquor | 164798022
West | Canned Goods | 163330813
West | Cleaning supplies | 148776443
West | Dairy | 145244575
West | Seafood | 139464407
West | Medical | 126184049
West | Pharmacy | 91628523
| | 5164234493
(43 rows)
INSERT statement that includes WITH clause
The following SQL uses a WITH clause to insert data from a JOIN query into table total_store_sales:
CREATE TABLE total_store_sales (store_key int, region VARCHAR(20), store_sales numeric (12,2));
INSERT INTO total_store_sales
WITH store_sales AS (
SELECT sd.store_key, sd.store_region::VARCHAR(20), SUM (of.total_order_cost)
FROM store.store_dimension sd JOIN store.store_orders_fact of ON sd.store_key = of.store_key
GROUP BY sd.store_region, sd.store_key ORDER BY sd.store_region, sd.store_key)
SELECT * FROM store_sales;
=> SELECT * FROM total_store_sales ORDER BY region, store_key;
store_key | region | store_sales
-----------+-----------+-------------
2 | East | 47668303.00
6 | East | 48136354.00
12 | East | 46673113.00
22 | East | 48711211.00
24 | East | 48603836.00
31 | East | 46836469.00
36 | East | 48461449.00
37 | East | 48018279.00
41 | East | 48713084.00
44 | East | 47808362.00
49 | East | 46990023.00
50 | East | 47643329.00
9 | MidWest | 46851087.00
15 | MidWest | 48787354.00
27 | MidWest | 48497620.00
29 | MidWest | 47639234.00
30 | MidWest | 49013483.00
38 | MidWest | 48856012.00
42 | MidWest | 47297912.00
45 | MidWest | 48544521.00
46 | MidWest | 48887255.00
4 | NorthWest | 47580215.00
39 | NorthWest | 47136892.00
47 | NorthWest | 48477574.00
8 | South | 48131455.00
13 | South | 47605422.00
17 | South | 46054367.00
…
(50 rows)