Put null values last when sorting (like Excel or Postgres)SQL

Editor's note: DuckDB enables you to configure whether NULL values are returned first or last in result sets by default. You can also specify it per query using NULLS LAST in the query ORDER BY clause. Note that NULLS LAST is now the default with 0.8.0+.

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PRAGMA default_null_order='NULLS LAST';

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Matt Holden

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-- create macro
CREATE OR REPLACE MACRO udf_products_in_year (v_year, v_category)
AS TABLE
SELECT 
	name, 
	category, 
	created_at
FROM products 
WHERE category = v_category
AND year(created_at) = v_year;

-- select using the macro as you would do from a table
SELECT *
FROM udf_products_in_year (2020, 'Home and Garden');

| Copper Light	| Home and Garden	| 2020-04-05 00:00:00.000 |
| Pink Armchair	| Home and Garden	| 2020-06-23 00:00:00.000 |

-- input ddl and data
CREATE TABLE products 
(
	name varchar,
	category varchar,
	created_at timestamp
);

INSERT INTO products
VALUES
('Cream Sofa', 'Home and Garden', '2019-03-14'),
('Copper Light', 'Home and Garden', '2020-04-05'),
('Pink Armchair', 'Home and Garden', '2020-06-23');

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Octavian Zarzu

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/* removes duplicate rows at the order_id level */
SELECT * FROM orders
QUALIFY row_number() over (partition by order_id order by created_at) = 1

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Octavian Zarzu

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Query Parquet data in S3Bash

Editor's note: DuckDB users often work with files in Parquet format, which has become a standard for representing data in data lakes. While DuckDB lets you work with local Parquet files, you can also use files stored in blob storage such as Amazon AWS S3, Azure Blob Storage and Google Cloud Storage.

Execute this Bash

# Assuming you have the following environment variables defined:
# AWS_ACCESS_KEY_ID
# AWS_SECRET_ACCESS_KEY
# AWS_DEFAULT_REGION
duckdb -c 'LOAD httpfs; SELECT count(*) FROM read_parquet("s3://<bucket>/<prefix>/*.parquet");'

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Damon

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SUMMARIZESQL

Editor's note: the SUMMARIZE() function allows you to quickly understand your data. If you want to understand a little more about how it works under the hood, see Hamilton's other snippet on building your own SUMMARIZE() capabilities using built-in analytics functions.

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SUMMARIZE some_tbl;
SUMMARIZE from 'some_file.csv';
--- summary informations about a given table

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Carlo Piovesan

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Compute a metric for each numeric column and return the values in a long table (requires 0.7.2+)SQL

Editor's note: if your data originates as different types or in a format like CSV, you might want to do so without risking throwing an error for oddly-typed values. You can do so with TRY_CAST(), which will attempt a CAST but return NULL if not possible.

Execute this SQL

with computed as (
    select sum(try_cast(columns(*) as double))
    from read_csv_auto('aapl.csv')
)

select
    -- restore original column names
    trim(list_element(regexp_extract_all(name,'\.(.*?) AS',1),1),'"') as name,
    value
from (pivot_longer computed on *)

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Ben Ayre

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Convert CSV to Parquet and provide schema to useBash

Editor's note: while there are other snippets showing file conversion, Parth's shows you how to convert from CSV to Parquet files using DuckDB with specification of the entire schema (columns) and compression codec.

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duckdb -c "COPY (SELECT * FROM read_csv('pageviews-sanitized-20230101-000000.csv', delim=' ', header=False, columns={'domain_code': 'VARCHAR', 'page_title': 'VARCHAR', 'count_views': 'UINTEGER', 'total_response_size': 'UINTEGER'})) TO 'pageviews-sanitized-20230101-000000.parquet' (FORMAT 'PARQUET', CODEC 'zstd')"

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Parth Patil

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Combine several parquet files into one and compress with zstdBash

Editor's note: another great example of using DuckDB's wide data format support to merge/combine multiple Parquet files. Parth also kindly shows you how to compress the resulting Parquet file with the zstd codec. DuckDB also supports gzip and snappy compression codecs.

Execute this Bash

duckdb -c "COPY (SELECT * FROM '~/Binance_Spot_Data/*.parquet') TO 'binance.parquet' (FORMAT 'PARQUET', CODEC 'zstd')"

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Parth Patil

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