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- Browsing Offline 13497
- You can browse the DuckDB documentation offline in the following formats: Single Markdown file (approx. 6 MB) PDF file (approx. 40 MB)
... - https://man.mtool.work/duckdb/2.0/guides/offline-copy.html
- DELETE Statement 11076
- The DELETE statement removes rows from the table identified by the table-name. If the WHERE clause is not present, all records in the table are deleted. If a WHERE clause is supplied, then only those rows for which the WHERE clause results
...(name VARCHAR, age INTEGER); INSERT INTO employees VALUES ('Kat', 32); DELETE FROM employees RETURNING name, 2025 - age AS approx_birthyear; name approx_birthyear Kat 1993 Syntax The TRUNCATE Statement The TRUNCATE statement removes all rows from a tab... - https://man.mtool.work/duckdb/2.0/sql/statements/delete.html
- Schema 10205
- Types It is important to use the correct type for encoding columns (e.g., BIGINT , DATE , DATETIME ). While it is always possible to use string types ( VARCHAR , etc.) to encode more specific values, this is not recommended. Strings use mor
...fference in aggregation speed using the creationDate column of the LDBC Comment table on scale factor 300 . This table has approx. 554 million unordered timestamp values. We run a simple aggregation query that returns the average day-of-the month from...the same for both experiments, their runtimes vary significantly. The results below show that joining on BIGINT columns is approx. 1.8× faster than performing the same join on VARCHAR -typed columns encoding the same value. Join column payload type Joi...imary Keys We illustrate the effect of using primary keys with the LDBC Comment table at scale factor 300 . This table has approx. 554 million entries. In the first experiment, we create the schema with a primary key, then load the data. In the second... - https://man.mtool.work/duckdb/2.0/guides/performance/schema.html
- Summarize 9700
- The SUMMARIZE command can be used to easily compute a number of aggregates over a table or a query. The SUMMARIZE command launches a query that computes a number of aggregates over all columns ( min , max , approx_unique , avg , std , q25 ,
...the column name, column type, and the percentage of NULL values in the column. Note that the quantiles and percentiles are approximate values . Usage To summarize the contents of a table, use SUMMARIZE followed by the table name. SUMMARIZE tbl; To summ...sing the tpch extension . INSTALL tpch; LOAD tpch; CALL dbgen(sf = 1); SUMMARIZE lineitem; column_name column_type min max approx_unique avg std q25 q50 q75 count null_percentage l_orderkey INTEGER 1 6000000 1508227 3000279.604204982 1732187.8734803519... - https://man.mtool.work/duckdb/2.0/guides/meta/summarize.html
- List Functions 9178
- Function Description list[index] Extracts a single list element using a (1-based) index . list[begin[:end][:step]] Extracts a sublist using slice conventions . Negative values are accepted. list1 && list2 Alias for list_has_any . list1 <->
...he list . list_append(list, element) Appends element to list . list_apply(list, lambda(x)) Alias for list_transform . list_approx_count_distinct(list) Applies aggregate function approx_count_distinct to the list . list_avg(list) Applies aggregate funct...to list . | | Example | list_append([2, 3], 4) | | Result | [2, 3, 4] | | Aliases | array_append , array_push_back | list_approx_count_distinct(list) | Description | Applies aggregate function approx_count_distinct to the list . | | Example | list_app...(column) as their argument. list_avg , list_var_samp , list_var_pop , list_stddev_pop , list_stddev_samp , list_sem , list_approx_count_distinct , list_bit_xor , list_bit_or , list_bit_and , list_bool_and , list_bool_or , list_count , list_entropy , li... - https://man.mtool.work/duckdb/2.0/sql/functions/list.html
- Aggregate Functions 9004
- Examples Produce a single row containing the sum of the amount column: SELECT sum(amount) FROM sales; Produce one row per unique region, containing the sum of amount for each group: SELECT region, sum(amount) FROM sales GROUP BY region; Ret
...l be skipped. This function is affected by ordering . | | Example | weighted_avg(A, W) | | Alias(es) | wavg(arg, weight) | Approximate Aggregates The table below shows the available approximate aggregate functions. Function Description Example approx_c...ount_distinct(x) Calculates the approximate count of distinct elements using HyperLogLog. approx_count_distinct(A) approx_quantile(x, pos) Calculates the approxi...mate quantile using T-Digest. approx_quantile(A, 0.5) approx_top_k(arg, k) Calculates a LIST of the k approximately most frequent values of arg using Filtered... - https://man.mtool.work/duckdb/2.0/sql/functions/aggregates.html
- Quack on WebAssembly 8133
- CloudFormation Stack We provide an example template for initializing a CloudFormation stack, based on pre-baked public AMI, based on Ubuntu, which will: via DuckDB, install and load Quack, create a randomized token, and do quack_serve on th
...me my-quack-demo \ --template-url https://duckdb-quack-ami.s3.us-east-1.amazonaws.com/quack.yaml \ --region us-east-2 Wait approx. 2 minutes for the deployment to complete (this command is blocking): aws cloudformation wait stack-create-complete \ --st... - https://man.mtool.work/duckdb/2.0/quack/setup/quack_wasm.html
- FROM and JOIN Clauses 7959
- The FROM clause specifies the source of the data on which the remainder of the query should operate. Logically, the FROM clause is where the query starts execution. The FROM clause can contain a single table, a combination of multiple table
...BY SIMILARITY ⟨expression⟩ (higher is closer) or NEAREST ⟨k⟩ BY DISTANCE ⟨expression⟩ (lower is closer). Prefixing it with APPROX performs an approximate search, which can be faster for large inputs: SELECT q.user_id, t.product_id FROM users q INNER JO...IN products t APPROX NEAREST 2 BY SIMILARITY array_cosine_similarity(q.embedding, t.embedding); Nearest joins can be combined with the regular... - https://man.mtool.work/duckdb/2.0/sql/query_syntax/from.html
- Python Client API 7610
- 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
...': ('list_aggregate', 0, ['ANY[]', 'VARCHAR']), 'any_value': ('list_any_value', 0, []), 'append': ('list_append', 0, []), 'approx_count_distinct': ('list_approx_count_distinct', 0, []), 'avg': ('list_avg', 0, []), 'bit_and': ('list_bit_and', 0, []), 'b...QL: list_any_value . append ( * args : ValueOrExpr ) → ListExpr The list_append function. Arguments: e. SQL: list_append . approx_count_distinct ( * args : ValueOrExpr ) → Expression An approximate count of the distinct elements. SQL: list_approx_count... - https://man.mtool.work/duckdb/2.0/clients/python/reference/
- PHP Client 7610
- The DuckDB PHP client is a tertiary client and is maintained by a third-party. Client API for PHP, focused on performance. The DuckDB PHP client uses the official C API internally through FFI , achieving good benchmark results. This library
...-------------------------------------------------------------------------------- | column_name | column_type | min | max | approx_unique | avg | std | q25 | q50 | q75 | count | null_percentage | ---------------------------------------------------------... - https://man.mtool.work/duckdb/2.0/clients/tertiary_clients/php.html
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