DOT_PRODUCT
DOT_PRODUCT(array, array) Computes the dot product of two vectors.
SELECT DOT_PRODUCT([1, 2, 3, 4], [5, 6, 7, 8])
70
(= 1 5 + 2 6 + 3 7 + 4 8)
SELECT DOT_PRODUCT([1.1, 2.2, 3.3, 4.4], [5.5, 6.6, 7.7, 8.8])
84.7
(= 1.1 5.5 + 2.2 6.6 + 3.3 7.7 + 4.4 8.8)
SELECT DOT_PRODUCT([5, 6], [1, 2, 3, 4])
Error: Cannot apply operation DOT_PRODUCT on vectors of different sizes 2 and 4.
EUCLIDEAN_DIST
EUCLIDEAN_DIST(array, array) Computes the Euclidean distance of two vectors (which is also referred to as the L2 norm). Euclidean distance represents the square root of the sum of squared differences between corresponding elements of two vectors.
SELECT EUCLIDEAN_DIST([1, 2, 3, 4], [5, 6, 7, 8])
8
SELECT EUCLIDEAN_DIST([1.1, 2.2, 3.3, 4.4], [5.5, 6.6, 7.7, 8.8])
8.8
SELECT EUCLIDEAN_DIST([1, 2, 3, 4], [5.5, 6.6, 7.7, 8.8])
9.302688
COSINE_SIM
COSINE_SIM(array, array) Computes the cosine similarity of two vectors. Cosine similarity represents the dot product of two vectors divided by their magnitude
SELECT COSINE_SIM([1, 2, 3, 4], [5, 6, 7, 8])
0.968864
SELECT COSINE_SIM([1.1, 2.2, 3.3, 4.4], [5.1, 6.2, 7.3, 8.4])
0.971264
SELECT COSINE_SIM([1.1, 2.2, 3.3, 4.4], [1, 1, 1, 1])
0.912871