Results of 1 - 10 of about 14 for Relational (0.008 sec.)
- Python Client API 14616
- 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
...step at a time; it runs only when a method reads its rows, and runs again on every read. Detailed examples can be found at Relational API page . aggregate ( aggr_expr : object , group_expr : object = '' ) → DuckDBPyRelation Compute the aggregate aggr_expr...by the optional groups group_expr on the relation. Detailed examples can be found at Relational API page . alias Get the name of the current alias. Detailed examples can be found at Relational API page . any_value ( ex...str = '' ) → DuckDBPyRelation Returns the first non-null value from a given expression. Detailed examples can be found at Relational API page . apply ( function_name : str , function_aggr : str , group_expr : str = '' , function_parameter : str = '' , pro... - https://man.mtool.work/duckdb/2.0/clients/python/reference/
- Relational API on Pandas 10415
- DuckDB offers a relational API that can be used to chain together query operations. These are lazily evaluated so that DuckDB can optimize their execution. These operators can act on Pandas DataFrames, DuckDB tables or views (which can poin
...["one", "two", "three", "four"]}) # create a DuckDB relation from a dataframe rel = con.from_df(input_df) # chain together relational operators (this is a lazy operation, so the operations are not yet executed) # equivalent to: SELECT i, j, i*2 AS two_i FR....df() could have been added to the end of the chain above - it was separated for clarity output_df = transformed_rel.df() Relational operators can also be used to group rows, aggregate, find distinct combinations of values, join, union and more. They are...also able to directly insert results into a DuckDB table or write to a CSV. Please see the Relational API page for more examples and the available relational methods on the DuckDBPyRelation class .... - https://man.mtool.work/duckdb/2.0/guides/python/relational_api_pandas.html
- Export to Apache Arrow 8857
- All results of a query can be exported to an Apache Arrow Table using the to_arrow_table function. Alternatively, results can be returned as a RecordBatchReader using the to_arrow_reader function and results can be read one batch at a time.
...Call these functions on the relation that duckdb.sql , con.sql or DuckDB's Relational API returns: its reader streams the result. On a con.execute() result they first copy all rows and warn with a UserWarning...{'i': [2, 3]} {'i': [4]} The small batch size makes the batches visible here. Omit it to use the default size. Export from Relational API Arrow objects can also be exported from the Relational API. A relation can be converted to an Arrow table using DuckDB... - https://man.mtool.work/duckdb/2.0/guides/python/export_arrow.html
- Guides 8437
- The guides section contains compact how-to guides that are focused on achieving a single goal. For API references and examples, see the rest of the documentation. Note that there are many tools using DuckDB, which are not covered in the off
...Arrow How to execute SQL on Apache Arrow How to create a DuckDB table from Apache Arrow How to export data to Apache Arrow Relational API How to query Pandas DataFrames with the Relational API Python Library Integrations How to use Ibis to query DuckDB wit... - https://man.mtool.work/duckdb/2.0/guides/overview.html
- INSERT Statements 8244
- INSERT statements are the standard way of loading data into a relational database. When using INSERT statements, the values are supplied row-by-row. While simple, there is significant overhead involved in parsing and processing individual I
... - https://man.mtool.work/duckdb/2.0/data/insert.html
- Spark API 8192
- The DuckDB Spark API implements the PySpark API , allowing you to use the familiar Spark API to interact with DuckDB. All statements are translated to DuckDB's internal plans using our relational API and executed using DuckDB's query engine
... - https://man.mtool.work/duckdb/2.0/clients/python/spark_api.html
- Conversion between DuckDB and Python 8052
- This page documents the rules for converting DuckDB results to Python and Python objects to DuckDB . Result Conversion: DuckDB Results to Python A result is read from a relation or, when using the DB-API / con.execute() , from the connectio
...n. con.sql() , con.table() , the readers and the other relational methods return relations. Each has its own methods: Result Relation DB-API 2.0 ( con.execute() ) Python tuples fetchall()...fetch_df_chunk() because it is stateless, i.e. it does not hold a result itself. To get specific rows of a result with the relational API you would use limit(n).fetchall() , iter_rows() or to_arrow_reader() instead. Note that with the DB-API, after a parti... - https://man.mtool.work/duckdb/2.0/clients/python/conversion.html
- SQL Introduction 8052
- This page provides an overview of how to perform simple operations in SQL. This tutorial is only intended to give you an introduction and is in no way a complete tutorial on SQL. This tutorial is adapted from the PostgreSQL tutorial . DuckD
...ge (SQL) More SQL (Subqueries + Embedded SQL) SQL: Grouping + Aggregation and Functional Dependencies Concepts DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essenti...no right-table match, empty (null) values are substituted for the right-table columns. Aggregate Functions Like most other relational database products, DuckDB supports aggregate functions. An aggregate function computes a single result from multiple input... - https://man.mtool.work/duckdb/2.0/sql/introduction.html
- FROM and JOIN Clauses 8052
- 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
...e side of the join instead of the final result set, without having to resort to sub-queries. Joins Joins are a fundamental relational operation used to connect two tables or relations horizontally. The relations are referred to as the left and right sides...sed using a loop: for (i = 0; i < n; i++) { f(t1.a[i], t2.b[i]); } It is difficult to express this in standard SQL because relational tables are not ordered, but imported tables such as data frames or disk files (like CSVs or Parquet files ) do have a natu... - https://man.mtool.work/duckdb/2.0/sql/query_syntax/from.html
- Migrating Python Code to DuckDB 2.0 7964
- This page lists what Python code written for DuckDB 1.x must change to run on DuckDB 2.0. Each item gives the 1.x form, the 2.0 form and the page that explains it. For changes outside the Python client, see Migrating to DuckDB v2.0 . Python
...drop , unnest , unpivot , preview and group_by , so rel.offset is the method. Write rel["offset"] for the column. See the Relational API . sql() of statements that do not read. 1.x: con.sql("CREATE TABLE t (i INTEGER)") returned None . 2.0: it returns a r... - https://man.mtool.work/duckdb/2.0/clients/python/migration.html
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