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- Metrics 12722
- DuckDB provides a set of metrics that can be used to monitor the performance and health of the database. Metrics are named ⟨group⟩.⟨metric⟩ , e.g., query.total_time or operator.timing . The set of collected metrics is controlled with the tr
...seconds CPU time spent on the query query.sql string The SQL string of the query query.total_intermediate_rows uint64 rows Cumulative number of intermediate rows produced by the query query.total_intermediate_size_bytes uint64 bytes Cumulative size in byte...s of all intermediate results produced by the query query.total_row_groups_scanned uint64 row_groups Cumulative number of row groups scanned by the query query.total_row_groups_to_scan uint64 row_groups Cumulative total number of row...groups available to scan query.total_rows_scanned uint64 rows Cumulative number of rows scanned by the query query.total_time double seconds Time spent executing the entire query system Metrics M... - https://man.mtool.work/duckdb/2.0/dev/metrics.html
- Profiling Queries 9578
- DuckDB supports profiling queries via the EXPLAIN and EXPLAIN ANALYZE statements. EXPLAIN To see the query plan of a query without executing it, run: EXPLAIN ⟨query⟩; The output of EXPLAIN contains the estimated cardinalities for each opera
...query⟩; The EXPLAIN ANALYZE statement runs the query, and shows the actual cardinalities for each operator, as well as the cumulative wall-clock time spent in each operator.... - https://man.mtool.work/duckdb/2.0/sql/statements/profiling.html
- EXPLAIN ANALYZE: Profile Queries 8956
- Prepending a query with EXPLAIN ANALYZE both pretty-prints the query plan, and executes it, providing run-time performance numbers and the actual cardinality (number of rows produced) for every operator. EXPLAIN ANALYZE SELECT * FROM tbl; N
...ote that the cumulative wall-clock time that is spent on every operator is shown. When multiple threads are processing the query in parallel, the... - https://man.mtool.work/duckdb/2.0/guides/meta/explain_analyze.html
- Window Functions 8956
- DuckDB supports window functions , which can use multiple rows to calculate a value for each row. Window functions are blocking operators , i.e., they require their entire input to be buffered, making them one of the most memory-intensive o
...unctions The table below shows the available general window functions. Name Description cume_dist([ORDER BY ordering]) The cumulative distribution: (number of partition rows preceding or peer with current row) / total partition rows. dense_rank() The rank...]) The number of the current row within the partition, counting from 1. cume_dist([ORDER BY ordering]) | Description | The cumulative distribution: (number of partition rows preceding or peer with current row) / total partition rows. If an ORDER BY clause...ER (WHERE x IS NOT NULL) ) ignore nulls and do not accept RESPECT NULLS . For example, sum(column) OVER (ORDER BY time) AS cumulativeColumn computes a cumulative sum where rows with a NULL value of column have the same value of cumulativeColumn as the row... - https://man.mtool.work/duckdb/2.0/sql/functions/window_functions.html
- Relational API 7494
- The Relational API builds a query one step at a time from Python. A relation, a DuckDBPyRelation , is a piece of SQL text: the methods of the Transformation and Functions sections return a new relation whose text extends the one they were c
...present in a given expression. count Computes the number of elements present in a given expression. cume_dist Computes the cumulative distribution within the partition. dense_rank Computes the dense rank within the partition. favg Computes the average of a...│ └───────────┘ cume_dist cume_dist(self, window_spec: str, projected_columns: str = '') -> DuckDBPyRelation Computes the cumulative distribution within the partition. Parameters window_spec : str Window specification, written as OVER (PARTITION BY ... OR... - https://man.mtool.work/duckdb/2.0/clients/python/relational_api.html
- Python Client API 7074
- Connection class duckdb. Appender Bases: object append_row ( self , * args ) → None Buffer one row, one value per column, each converted as an executemany parameter would be append_rows ( self , rows : object ) → None Buffer each row of an
...nd at Relational API page . cume_dist ( window_spec : str , projected_columns : str = '' ) → DuckDBPyRelation Computes the cumulative distribution within the partition. Detailed examples can be found at Relational API page . dense_rank ( window_spec : str... - https://man.mtool.work/duckdb/2.0/clients/python/reference/
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