SELECT vec_to_string(parse_vec('[1.0, 2.0]')); SELECT vec_to_string(parse_vec('[1.0, 2.0, 3.0]')); SELECT vec_to_string(parse_vec('[]')); SELECT vec_to_string(vec_add('[1.0, 2.0]', '[3.0, 4.0]')); SELECT vec_to_string(vec_add(parse_vec('[1.0, 2.0]'), '[3.0, 4.0]')); SELECT vec_to_string(vec_add('[1.0, 2.0]', parse_vec('[3.0, 4.0]'))); SELECT vec_to_string(vec_mul('[1.0, 2.0]', '[3.0, 4.0]')); SELECT vec_to_string(vec_mul(parse_vec('[1.0, 2.0]'), '[3.0, 4.0]')); SELECT vec_to_string(vec_mul('[1.0, 2.0]', parse_vec('[3.0, 4.0]'))); SELECT vec_to_string(vec_sub('[1.0, 1.0]', '[1.0, 2.0]')); SELECT vec_to_string(vec_sub('[-1.0, -1.0]', '[1.0, 2.0]')); SELECT vec_to_string(vec_sub('[1.0, 1.0]', parse_vec('[1.0, 2.0]'))); SELECT vec_to_string(vec_sub('[-1.0, -1.0]', parse_vec('[1.0, 2.0]'))); SELECT vec_to_string(vec_sub(parse_vec('[1.0, 1.0]'), '[1.0, 2.0]')); SELECT vec_to_string(vec_sub(parse_vec('[-1.0, -1.0]'), '[1.0, 2.0]')); SELECT vec_elem_sum('[1.0, 2.0, 3.0]'); SELECT vec_elem_sum('[-1.0, -2.0, -3.0]'); SELECT vec_elem_sum(parse_vec('[1.0, 2.0, 3.0]')); SELECT vec_elem_sum(parse_vec('[-1.0, -2.0, -3.0]')); SELECT vec_elem_avg('[1.0, 2.0, 3.0]'); SELECT vec_elem_avg('[-1.0, -2.0, -3.0]'); SELECT vec_elem_avg(parse_vec('[1.0, 2.0, 3.0]')); SELECT vec_elem_avg(parse_vec('[-1.0, -2.0, -3.0]')); SELECT vec_to_string(vec_div('[1.0, 2.0]', '[3.0, 4.0]')); SELECT vec_to_string(vec_div(parse_vec('[1.0, 2.0]'), '[3.0, 4.0]')); SELECT vec_to_string(vec_div('[1.0, 2.0]', parse_vec('[3.0, 4.0]'))); SELECT vec_to_string(vec_div('[1.0, -2.0]', parse_vec('[0.0, 0.0]'))); SELECT vec_elem_product('[1.0, 2.0, 3.0, 4.0]'); SELECT vec_elem_product('[-1.0, -2.0, -3.0, 4.0]'); SELECT vec_elem_product(parse_vec('[1.0, 2.0, 3.0, 4.0]')); SELECT vec_elem_product(parse_vec('[-1.0, -2.0, -3.0, 4.0]')); SELECT vec_to_string(vec_norm('[0.0, 2.0, 3.0]')); SELECT vec_to_string(vec_norm('[1.0, 2.0, 3.0]')); SELECT vec_to_string(vec_norm('[7.0, 8.0, 9.0]')); SELECT vec_to_string(vec_norm('[7.0, -8.0, 9.0]')); SELECT vec_to_string(vec_norm(parse_vec('[7.0, -8.0, 9.0]'))); SELECT vec_to_string(vec_sum(v)) FROM ( SELECT '[1.0, 2.0, 3.0]' AS v UNION ALL SELECT '[-1.0, -2.0, -3.0]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0]' AS v ); SELECT vec_to_string(vec_avg(v)) FROM ( SELECT '[1.0, 2.0, 3.0]' AS v UNION ALL SELECT '[10.0, 11.0, 12.0]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0]' AS v ); SELECT vec_to_string(vec_product(v)) FROM ( SELECT '[1.0, 2.0, 3.0]' AS v UNION ALL SELECT '[-1.0, -2.0, -3.0]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0]' AS v ); SELECT vec_dim('[7.0, 8.0, 9.0, 10.0]'); SELECT v, vec_dim(v) FROM ( SELECT '[1.0, 2.0, 3.0]' AS v UNION ALL SELECT '[-1.0]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0]' AS v ) Order By vec_dim(v) ASC; SELECT v, vec_dim(v) FROM ( SELECT '[1.0, 2.0, 3.0]' AS v UNION ALL SELECT '[-1.0]' AS v UNION ALL SELECT '[7.0, 8.0, 9.0, 10.0]' AS v ) Order By vec_dim(v) ASC; SELECT vec_kth_elem('[1.0, 2.0, 3.0]', 2); SELECT v, vec_kth_elem(v, 0) AS first_elem FROM ( SELECT '[1.0, 2.0, 3.0]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0, 7.0]' AS v UNION ALL SELECT '[8.0]' AS v ) WHERE vec_kth_elem(v, 0) > 2.0 ORDER BY first_elem; SELECT vec_to_string(vec_subvector('[1.0,2.0,3.0,4.0,5.0]', 0, 3)); SELECT vec_to_string(vec_subvector('[1.0,2.0,3.0,4.0,5.0]', 5, 5)); SELECT v, vec_to_string(vec_subvector(v, 3, 5)) FROM ( SELECT '[1.0, 2.0, 3.0, 4.0, 5.0]' AS v UNION ALL SELECT '[-1.0, -2.0, -3.0, -4.0, -5.0, -6.0]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0, 10, -8, 100]' AS v ) ORDER BY v; SELECT vec_to_string(vec_subvector(v, 0, 5)) FROM ( SELECT '[1.1, 2.2, 3.3, 4.4, 5.5]' AS v UNION ALL SELECT '[-1.1, -2.1, -3.1, -4.1, -5.1, -6.1]' AS v UNION ALL SELECT '[4.0, 5.0, 6.0, 10, -8, 100]' AS v ) ORDER BY v; SELECT h, vec_to_string(vec_sum(v)), vec_to_string(vec_avg(v)), vec_to_string(vec_product(v)) FROM ( SELECT 'a' AS h, '[1.0, 1.0]' AS v UNION ALL SELECT 'a' AS h, '[2.0, 2.0]' AS v UNION ALL SELECT 'b' AS h, '[3.0, 3.0]' AS v ) GROUP BY h ORDER BY h; -- On partitioned tables the aggregates are split into partial state and merge. -- Rows only land in two of the three partitions, the third one has an empty state. -- The two non-empty partitions differ in row count and mean, so vec_avg must weight by count. CREATE TABLE vector_aggr_partitioned ( ts TIMESTAMP TIME INDEX, k INT, g STRING, v VECTOR(2), PRIMARY KEY(k) ) PARTITION ON COLUMNS (k) (k < 10, k >= 10 AND k < 20, k >= 20); INSERT INTO vector_aggr_partitioned VALUES (1000, 1, 'a', '[1.0, 1.0]'), (2000, 11, 'a', '[8.0, 8.0]'), (3000, 2, 'a', '[3.0, 3.0]'), (3500, 3, 'a', '[5.0, 5.0]'), (4000, 12, 'b', '[4.0, 4.0]'); SELECT vec_to_string(vec_sum(v)), vec_to_string(vec_avg(v)), vec_to_string(vec_product(v)) FROM vector_aggr_partitioned; SELECT g, vec_to_string(vec_sum(v)), vec_to_string(vec_avg(v)), vec_to_string(vec_product(v)) FROM vector_aggr_partitioned GROUP BY g ORDER BY g; -- A NULL vector makes vec_sum and vec_product NULL, vec_avg skips it. INSERT INTO vector_aggr_partitioned VALUES (5000, 21, 'b', NULL); SELECT vec_to_string(vec_sum(v)), vec_to_string(vec_avg(v)), vec_to_string(vec_product(v)) FROM vector_aggr_partitioned; SELECT g, vec_to_string(vec_sum(v)), vec_to_string(vec_avg(v)), vec_to_string(vec_product(v)) FROM vector_aggr_partitioned GROUP BY g ORDER BY g; DROP TABLE vector_aggr_partitioned;