INFER_SCHEMA
Automatically detects the file metadata schema and retrieves the column definitions.
infer_schema
currently supports the following file formats:
- Parquet - Native support for schema inference
- CSV - With customizable delimiters and header detection
- NDJSON - Newline-delimited JSON files
Compression Support: All formats also support compressed files with extensions .zip
, .xz
, .zst
.
Each individual file has a maximum size limit of 100MB for schema inference.
When processing multiple files, infer_schema
automatically merges different schemas:
- Compatible types are promoted (e.g., INT8 + INT16 → INT16)
- Incompatible types fall back to VARCHAR (e.g., INT + FLOAT → VARCHAR)
- Missing columns in some files are marked as nullable
- New columns from later files are added to the final schema
This ensures all files can be read using the unified schema.
Syntax
INFER_SCHEMA(
LOCATION => '{ internalStage | externalStage }'
[ PATTERN => '<regex_pattern>']
[ FILE_FORMAT => '<format_name>' ]
[ MAX_RECORDS_PRE_FILE => <number> ]
[ MAX_FILE_COUNT => <number> ]
)
Parameters
Parameter | Description | Default | Example |
---|---|---|---|
LOCATION | Stage location: @<stage_name>[/<path>] | Required | '@my_stage/data/' |
PATTERN | File name pattern to match | All files | '*.csv' , '*.parquet' |
FILE_FORMAT | File format name for parsing | Stage's format | 'csv_format' , 'NDJSON' |
MAX_RECORDS_PRE_FILE | Max records to sample per file | All records | 100 , 1000 |
MAX_FILE_COUNT | Max number of files to process | All files | 5 , 10 |
Examples
Parquet Files
-- Create stage and export data
CREATE STAGE test_parquet;
COPY INTO @test_parquet FROM (SELECT number FROM numbers(10)) FILE_FORMAT = (TYPE = 'PARQUET');
-- Infer schema from parquet files using pattern
SELECT * FROM INFER_SCHEMA(
location => '@test_parquet',
pattern => '*.parquet'
);
Result:
+-------------+-----------------+----------+----------+----------+
| column_name | type | nullable | filenames| order_id |
+-------------+-----------------+----------+----------+----------+
| number | BIGINT UNSIGNED | false | data_... | 0 |
+-------------+-----------------+----------+----------+----------+
CSV Files
-- Create stage and export CSV data
CREATE STAGE test_csv;
COPY INTO @test_csv FROM (SELECT number FROM numbers(10)) FILE_FORMAT = (TYPE = 'CSV');
-- Create a CSV file format
CREATE FILE FORMAT csv_format TYPE = 'CSV';
-- Infer schema using pattern and file format
SELECT * FROM INFER_SCHEMA(
location => '@test_csv',
pattern => '*.csv',
file_format => 'csv_format'
);
Result:
+-------------+---------+----------+----------+----------+
| column_name | type | nullable | filenames| order_id |
+-------------+---------+----------+----------+----------+
| column_1 | BIGINT | true | data_... | 0 |
+-------------+---------+----------+----------+----------+
For CSV files with headers:
-- Create CSV file format with header support
CREATE FILE FORMAT csv_headers_format
TYPE = 'CSV'
field_delimiter = ','
skip_header = 1;
-- Export data with headers
CREATE STAGE test_csv_headers;
COPY INTO @test_csv_headers FROM (
SELECT number as user_id, 'user_' || number::string as user_name
FROM numbers(5)
) FILE_FORMAT = (TYPE = 'CSV', output_header = true);
-- Infer schema with headers
SELECT * FROM INFER_SCHEMA(
location => '@test_csv_headers',
file_format => 'csv_headers_format'
);
Limit records for faster inference:
-- Sample only first 5 records for schema inference
SELECT * FROM INFER_SCHEMA(
location => '@test_csv',
pattern => '*.csv',
file_format => 'csv_format',
max_records_pre_file => 5
);
NDJSON Files
-- Create stage and export NDJSON data
CREATE STAGE test_ndjson;
COPY INTO @test_ndjson FROM (SELECT number FROM numbers(10)) FILE_FORMAT = (TYPE = 'NDJSON');
-- Infer schema using pattern and NDJSON format
SELECT * FROM INFER_SCHEMA(
location => '@test_ndjson',
pattern => '*.ndjson',
file_format => 'NDJSON'
);
Result:
+-------------+---------+----------+----------+----------+
| column_name | type | nullable | filenames| order_id |
+-------------+---------+----------+----------+----------+
| number | BIGINT | true | data_... | 0 |
+-------------+---------+----------+----------+----------+
Limit records for faster inference:
-- Sample only first 5 records for schema inference
SELECT * FROM INFER_SCHEMA(
location => '@test_ndjson',
pattern => '*.ndjson',
file_format => 'NDJSON',
max_records_pre_file => 5
);
Schema Merging with Multiple Files
When files have different schemas, infer_schema
merges them intelligently:
-- Suppose you have multiple CSV files with different schemas:
-- file1.csv: id(INT), name(VARCHAR)
-- file2.csv: id(INT), name(VARCHAR), age(INT)
-- file3.csv: id(FLOAT), name(VARCHAR), age(INT)
SELECT * FROM INFER_SCHEMA(
location => '@my_stage/',
pattern => '*.csv',
file_format => 'csv_format'
);
Result shows merged schema:
+-------------+---------+----------+-----------+----------+
| column_name | type | nullable | filenames | order_id |
+-------------+---------+----------+-----------+----------+
| id | VARCHAR | true | file1,... | 0 | -- INT+FLOAT→VARCHAR
| name | VARCHAR | true | file1,... | 1 |
| age | BIGINT | true | file1,... | 2 | -- Missing in file1→nullable
+-------------+---------+----------+-----------+----------+
Pattern Matching and File Limits
Use pattern matching to infer schema from multiple files:
-- Infer schema from all CSV files in the directory
SELECT * FROM INFER_SCHEMA(
location => '@my_stage/',
pattern => '*.csv'
);
Limit the number of files processed to improve performance:
-- Process only the first 5 matching files
SELECT * FROM INFER_SCHEMA(
location => '@my_stage/',
pattern => '*.csv',
max_file_count => 5
);
Compressed Files
infer_schema
automatically handles compressed files:
-- Works with compressed CSV files
SELECT * FROM INFER_SCHEMA(location => '@my_stage/data.csv.zip');
-- Works with compressed NDJSON files
SELECT * FROM INFER_SCHEMA(
location => '@my_stage/data.ndjson.xz',
file_format => 'NDJSON',
max_records_pre_file => 50
);
Create Table from Inferred Schema
The infer_schema
function displays the schema but doesn't create tables. To create a table from the inferred schema:
-- Create table structure from file schema
CREATE TABLE my_table AS
SELECT * FROM @my_stage/ (pattern=>'*.parquet')
LIMIT 0;
-- Verify the table structure
DESC my_table;