Results of 1 - 10 of about 20 for short (0.001 sec.)
- Create Synthetic Data 14172
- DuckDB lets you quickly generate synthetic datasets by combining a few building blocks: functions and clauses that generate rows , functions that generate values to fill those rows, and extensions that generate whole benchmark datasets. Thi
...m duckdb.sqltypes import * from faker import Faker fake = Faker() def random_date(): return fake.date_between() def random_short_text(): return fake.text(max_nb_chars=20) def random_long_text(): return fake.text(max_nb_chars=200) con = duckdb.connect(...) con.create_function("random_date", random_date, [], DATE, type="native", side_effects=True) con.create_function("random_short_text", random_short_text, [], VARCHAR, type="native", side_effects=True) con.create_function("random_long_text", random_lo...type="native", side_effects=True) res = con.sql(""" SELECT hash(i * 10 + j) AS id, random_date() AS creation_date, random_short_text() AS short, random_long_text() AS long, IF (j % 2, TRUE, FALSE) AS bool FROM generate_series(1, 5) s(i) CROSS JOIN ge... - https://man.mtool.work/duckdb/2.0/guides/snippets/create_synthetic_data.html
- Jupyter Notebooks 11402
- DuckDB's Python client can be used directly in Jupyter notebooks with no additional configuration, as the first section shows. Additional libraries can simplify SQL query development; the rest of this guide uses the JupySQL package. See oth
...This tells JupySQL to store the query, but skips execution. It will be referenced in the next plotting call. %%sql --save short_trips --no-execute SELECT * FROM 'https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2021-01.parquet' WHERE t...ogram, call %sqlplot histogram and pass the name of the table, the column to plot and the number of bins. This uses --with short_trips so JupySQL uses the query defined previously and therefore only plots a subset of the data. %sqlplot histogram --tab...le short_trips --column trip_distance --bins 10 --with short_trips Summary You now have the ability to alternate between SQL and Pa... - https://man.mtool.work/duckdb/2.0/guides/python/jupyter.html
- Sharing Macros 10417
- DuckDB has a powerful macro mechanism that allows creating shorthands for common tasks. Sharing a Scalar Macro First, we define a macro that pretty-prints a non-negative integer as a short string with thousands, millions, and billions (with
...739957162925925638303138 code = 126327004005066229305810236187733612209 uic = 194659031858447341987368539307022394076 name_short = 225741449355216776462496463050578341773 name_medium = 339714102140420031901247247513112906072 name_long = 12607995628072... - https://man.mtool.work/duckdb/2.0/guides/snippets/sharing_macros.html
- AWS Extension 9822
- The aws extension adds functionality, e.g., authentication, on top of the httpfs extension's S3 capabilities , using the AWS SDK. Installing and Loading The aws extension will be transparently autoloaded on first use from the official exten
...ials obtained through AWS IAM Identity Center (formerly AWS SSO). DuckDB does not perform the sign-in itself: it reads the short-lived token that the AWS CLI caches after you sign in. The setup therefore has three steps. First, configure an SSO-enable...in, REFRESH auto ); When CHAIN is sts or web_identity , REFRESH auto is enabled automatically, since these credentials are short-lived. Amazon RDS (IAM Authentication) The aws extension can generate short-lived IAM authentication tokens for connecting... - https://man.mtool.work/duckdb/2.0/core_extensions/aws.html
- Amazon RDS with IAM Authentication 8632
- Managed PostgreSQL databases on Amazon RDS and Aurora can authenticate with short-lived IAM tokens instead of a static password. DuckDB supports this through the postgres and aws extensions: the aws extension generates the token from an AWS
... - https://man.mtool.work/duckdb/2.0/guides/database_integration/rds_iam.html
- Out-of-Memory Issues 8632
- Configuration Options If you are experiencing out-of-memory issues with DuckDB, try tweaking the following configuration options: Reduce the number of threads using the SET threads = ... command. Setting the memory limit lower than the defa
...large amount of data, try setting the preserve_insertion_order option to false : SET preserve_insertion_order = false . In short, try the settings: SET threads = ⟨lower_than_the_number_of_available_threads⟩; SET memory_limit = ⟨lower_than_80%_of_syste... - https://man.mtool.work/duckdb/2.0/guides/performance/oom.html
- UI Extension 8038
- The ui extension adds a user interface for your local DuckDB instance. Usage To start the UI from the command line: duckdb -ui To start the UI from SQL: CALL start_ui(); Running either of these will open the UI in your default browser. The
...detects when you connect to MotherDuck. These checks take very little time to complete, so the default polling interval is short (284 milliseconds). You can configure it with a SQL command like: SET ui_polling_interval = 284; The environment variable... - https://man.mtool.work/duckdb/2.0/core_extensions/ui.html
- Guides 8038
- 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
...icial guides. To find a list of these tools, check out the Awesome DuckDB repository . Tip For a short introductory tutorial, check out the “Analyzing Railway Traffic in the Netherlands” tutorial. Data Import and Export Data... - https://man.mtool.work/duckdb/2.0/guides/overview.html
- Appender 7834
- The Appender can be used to load bulk data into a DuckDB database. It is available in the C, C++, Go, Java, Julia, Node.js, Python, and Rust clients. This page describes how the Appender behaves across clients and shows a minimal example in
...he internal duckdb::Value type, however, this adds some additional overheads and should be avoided if possible. Below is a short example: con.Query("CREATE TABLE dates (d DATE, t TIME, ts TIMESTAMP)"); Appender appender(con, "dates"); // construct the... - https://man.mtool.work/duckdb/2.0/data/appender.html
- Execution Format 7834
- Vector is the container format used to store in-memory data during execution. DataChunk is a collection of Vectors, used for instance to represent a column list in a PhysicalProjection operator. Data Flow DuckDB uses a vectorized query exec
...uint32_t length; char prefix[4]; char *ptr; } pointer; struct { uint32_t length; char inlined[12]; } inlined; } value; }; Short strings ( <= 12 bytes ) are inlined into the structure, while larger strings are stored with a pointer to the data in the... - https://man.mtool.work/duckdb/2.0/internals/vector.html
DuckDB 2.0 Documentation / man.mtool.work