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Idiomatic Materialize SQL chart

Materialize follows the SQL standard (SQL-92) implementation and strives for compatibility with the PostgreSQL dialect. However, for some use cases, Materialize provides its own idiomatic query patterns that can provide better performance.

General

Query Patterns

Idiomatic Materialize SQL Pattern
ANY() Equi-join condition

If no duplicates in the unnested field

WITH my_expanded_values AS (SELECT UNNEST(array|list|map) AS fieldZ FROM tableB) SELECT a.fieldA, ... FROM tableA a JOIN my_expanded_values t ON a.fieldZ = t.fieldZ ;

If duplicates exist in the unnested field

WITH my_expanded_values AS (SELECT DISTINCT UNNEST(array|list|map) AS fieldZ FROM tableB) SELECT a.fieldA, ... FROM tableA a JOIN my_expanded_values t ON a.fieldZ = t.fieldZ ;

Examples

Idiomatic Materialize SQL
ANY() Equi-join condition

If no duplicates in the unnested field

-- sales_items.items contains no duplicates. --  WITH individual_sales_items AS (SELECT unnest(items) as item, week_of FROM sales_items) SELECT s.week_of, o.order_id, o.item, o.quantity FROM orders o JOIN individual_sales_items s ON o.item = s.item WHERE date_trunc('week', o.order_date) = s.week_of;

If duplicates exist in the unnested field

-- sales_items.items may contains duplicates --  WITH individual_sales_items AS (SELECT DISTINCT unnest(items) as item, week_of FROM sales_items) SELECT s.week_of, o.order_id, o.item, o.quantity FROM orders o JOIN individual_sales_items s ON o.item = s.item WHERE date_trunc('week', o.order_date) = s.week_of ORDER BY s.week_of, o.order_id, o.item, o.quantity ;

Window Functions

Materialize and window functions

For window functions, when an input record in a partition (as determined by the PARTITION BY clause of your window function) is added/removed/changed, Materialize recomputes the results for the entire window partition. This means that when a new batch of input data arrives (that is, every second), the amount of computation performed is proportional to the total size of the touched partitions.

For example, assume that in a given second, 20 input records change, and these records belong to 10 different partitions, where the average size of each partition is 100. Then, amount of work to perform is proportional to computing the window function results for 10*100=1000 rows.

As a rule of thumb, if the total size of all touched window partitions is at most 1000000 rows per second, then the system should be able to keep up with the input data as it arrives. However, if your use case has higher performance requirements, consider rewriting your query to not use window functions. If your query cannot be rewritten without the window functions and the performance of window functions is insufficient for your use case, please contact our team.

Query Patterns

Idiomatic Materialize SQL Pattern
Top-K over partition
(K >= 1)		 
SELECT fieldA, fieldB, ... FROM (SELECT DISTINCT fieldA FROM tableA) grp,  LATERAL (SELECT fieldB, ... , fieldZ FROM tableA  WHERE fieldA = grp.fieldA  ORDER BY fieldZ ... LIMIT K) -- K is a number >= 1 ORDER BY fieldA, fieldZ ... ;
Top-K over partition
(K = 1)		 
SELECT DISTINCT ON(fieldA) fieldA, fieldB, ... FROM tableA ORDER BY fieldA, fieldZ ... -- Top-K where K is 1;
First value over partition
order by ... 
SELECT tableA.fieldA, tableA.fieldB, minmax.Z  FROM tableA,  (SELECT fieldA,  MIN(fieldZ) -- Or MAX()  FROM tableA  GROUP BY fieldA) minmax WHERE tableA.fieldA = minmax.fieldA ORDER BY fieldA ... ;
Last value over partition
order by ...
range between unbounded preceding
and unbounded following		 
SELECT tableA.fieldA, tableA.fieldB, minmax.Z  FROM tableA,  (SELECT fieldA,  MAX(fieldZ) -- Or MIN()  FROM tableA  GROUP BY fieldA) minmax WHERE tableA.fieldA = minmax.fieldA ORDER BY fieldA ... ;

Lag over (order by) whose ordering can be represented by some equality condition.

To exclude the first row since it has no previous row

SELECT t1.fieldA, t2.fieldB FROM tableA t1, tableA t2 WHERE t1.fieldA = t2.fieldA + ... ORDER BY fieldA;

To include the first row

SELECT t1.fieldA, t2.fieldB FROM tableA t1 LEFT JOIN tableA t2 ON t1.fieldA = t2.fieldA + ... ORDER BY fieldA;

Lead over (order by) whose ordering can be represented by some equality condition.

To exclude the last row since it has no next row

SELECT t1.fieldA, t2.fieldB FROM tableA t1, tableA t2 WHERE t1.fieldA = t2.fieldA - ... ORDER BY fieldA;

To include the last row

SELECT t1.fieldA, t2.fieldB FROM tableA t1 LEFT JOIN tableA t2 ON t1.fieldA = t2.fieldA - ... ORDER BY fieldA;

Examples

Idiomatic Materialize SQL
Top-K over partition
(K >= 1)		 
SELECT order_id, item, subtotal FROM (SELECT DISTINCT order_id FROM orders_view) grp,  LATERAL (SELECT item, subtotal FROM orders_view  WHERE order_id = grp.order_id  ORDER BY subtotal DESC LIMIT 3) -- For Top 3 ORDER BY order_id, subtotal DESC;
Top-K over partition
(K = 1)		 
SELECT DISTINCT ON(order_id) order_id, item, subtotal FROM orders_view ORDER BY order_id, subtotal DESC; -- For Top 1
First value over partition
order by ...		 
SELECT o.order_id, minmax.lowest_price, minmax.highest_price,  o.item,  o.price,  o.price - minmax.lowest_price AS diff_lowest_price,  o.price - minmax.highest_price AS diff_highest_price FROM orders_view o,  (SELECT order_id,  MIN(price) AS lowest_price,  MAX(price) AS highest_price  FROM orders_view  GROUP BY order_id) minmax WHERE o.order_id = minmax.order_id ORDER BY o.order_id, o.item;
Last value over partition
order by...
range between unbounded preceding
and unbounded following		 
SELECT o.order_id, minmax.lowest_price, minmax.highest_price,  o.item,  o.price,  o.price - minmax.lowest_price AS diff_lowest_price,  o.price - minmax.highest_price AS diff_highest_price FROM orders_view o,  (SELECT order_id,  MIN(price) AS lowest_price,  MAX(price) AS highest_price  FROM orders_view  GROUP BY order_id) minmax WHERE o.order_id = minmax.order_id ORDER BY o.order_id, o.item;

Lag over (order by) whose ordering can be represented by some equality condition.

If suppressing the first row since it has no previous row

SELECT o1.order_date, o1.daily_total,  o2.daily_total as previous_daily_total FROM orders_daily_totals o1, orders_daily_totals o2 WHERE o1.order_date = o2.order_date + INTERVAL '1' DAY ORDER BY order_date;

To include the first row

SELECT o1.order_date, o1.daily_total,  o2.daily_total as previous_daily_total FROM orders_daily_totals o1 LEFT JOIN orders_daily_totals o2 ON o1.order_date = o2.order_date + INTERVAL '1' DAY ORDER BY order_date;

Lead over (order by) whose ordering can be represented by some equality condition.

To suppress the last row since it has no next row

SELECT o1.order_date, o1.daily_total,  o2.daily_total as previous_daily_total FROM orders_daily_totals o1, orders_daily_totals o2 WHERE o1.order_date = o2.order_date - INTERVAL '1' DAY ORDER BY order_date;

To include the last row

SELECT o1.order_date, o1.daily_total,  o2.daily_total as previous_daily_total FROM orders_daily_totals o1 LEFT JOIN orders_daily_totals o2 ON o1.order_date = o2.order_date - INTERVAL '1' DAY ORDER BY order_date;

See also

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