Window Functions interview questions

1. A.SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows
2. B.divides rows into groups within which a window function operates
3. C.a function computing across a set of rows related to the current row without collapsing them
4. D.RANK leaves gaps in numbering after ties; DENSE_RANK does not

Answer + AI explanation with Pro

1. A.Window function
2. B.ROW_NUMBER
3. C.Running total
4. D.LAG / LEAD

Answer + AI explanation with Pro

1. A.Window function — divides rows into groups within which a window function operates
2. B.Window function — SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows
3. C.Window function — a function computing across a set of rows related to the current row without collapsing them
4. D.Window function — assigns a unique sequential number to rows within a partition

Answer + AI explanation with Pro

1. A.divides rows into groups within which a window function operates
2. B.assigns a unique sequential number to rows within a partition
3. C.a function computing across a set of rows related to the current row without collapsing them
4. D.RANK leaves gaps in numbering after ties; DENSE_RANK does not

Answer + AI explanation with Pro

1. A.LAG / LEAD
2. B.RANK vs DENSE_RANK
3. C.ROW_NUMBER
4. D.PARTITION BY

Answer + AI explanation with Pro

1. A.ROW_NUMBER — a function computing across a set of rows related to the current row without collapsing them
2. B.ROW_NUMBER — RANK leaves gaps in numbering after ties; DENSE_RANK does not
3. C.ROW_NUMBER — SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows
4. D.ROW_NUMBER — assigns a unique sequential number to rows within a partition

Answer + AI explanation with Pro

1. A.assigns a unique sequential number to rows within a partition
2. B.divides rows into groups within which a window function operates
3. C.a function computing across a set of rows related to the current row without collapsing them
4. D.RANK leaves gaps in numbering after ties; DENSE_RANK does not

Answer + AI explanation with Pro

1. A.Running total
2. B.ROW_NUMBER
3. C.RANK vs DENSE_RANK
4. D.PARTITION BY

Answer + AI explanation with Pro

1. A.RANK vs DENSE_RANK — access a value from a previous or following row within the partition
2. B.RANK vs DENSE_RANK — divides rows into groups within which a window function operates
3. C.RANK vs DENSE_RANK — RANK leaves gaps in numbering after ties; DENSE_RANK does not
4. D.RANK vs DENSE_RANK — SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows

Answer + AI explanation with Pro

1. A.access a value from a previous or following row within the partition
2. B.a function computing across a set of rows related to the current row without collapsing them
3. C.divides rows into groups within which a window function operates
4. D.assigns a unique sequential number to rows within a partition

Answer + AI explanation with Pro

1. A.LAG / LEAD
2. B.PARTITION BY
3. C.Running total
4. D.RANK vs DENSE_RANK

Answer + AI explanation with Pro

1. A.PARTITION BY — a function computing across a set of rows related to the current row without collapsing them
2. B.PARTITION BY — assigns a unique sequential number to rows within a partition
3. C.PARTITION BY — RANK leaves gaps in numbering after ties; DENSE_RANK does not
4. D.PARTITION BY — divides rows into groups within which a window function operates

Answer + AI explanation with Pro

1. A.a function computing across a set of rows related to the current row without collapsing them
2. B.access a value from a previous or following row within the partition
3. C.divides rows into groups within which a window function operates
4. D.RANK leaves gaps in numbering after ties; DENSE_RANK does not

Answer + AI explanation with Pro

1. A.LAG / LEAD
2. B.RANK vs DENSE_RANK
3. C.ROW_NUMBER
4. D.PARTITION BY

Answer + AI explanation with Pro

1. A.LAG / LEAD — SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows
2. B.LAG / LEAD — assigns a unique sequential number to rows within a partition
3. C.LAG / LEAD — access a value from a previous or following row within the partition
4. D.LAG / LEAD — divides rows into groups within which a window function operates

Answer + AI explanation with Pro

1. A.assigns a unique sequential number to rows within a partition
2. B.access a value from a previous or following row within the partition
3. C.a function computing across a set of rows related to the current row without collapsing them
4. D.SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows

Answer + AI explanation with Pro

1. A.Running total
2. B.RANK vs DENSE_RANK
3. C.PARTITION BY
4. D.ROW_NUMBER

Answer + AI explanation with Pro

1. A.Running total — divides rows into groups within which a window function operates
2. B.Running total — SUM(...) OVER (ORDER BY ...) that accumulates values across ordered rows
3. C.Running total — access a value from a previous or following row within the partition
4. D.Running total — assigns a unique sequential number to rows within a partition

Answer + AI explanation with Pro