Load Metadata and File-Based Partitioned Data in Data Pipelines

the data pipeline loading infrastructure enables the loading of certain metadata values of a source record into the {{ocient}} system metadata represents information about a record that is not represented in the record data itself, e g , the filename of the source record or the timestamp when a record was created in {{kafka}} you can also load data in partitioned files using {{hive}} naming standards with a filter set in the file path syntaxes the metadata function can load a variety of metadata along with each record of the data pipeline, or it can use key value pairs to return the value in the filename metadata load metadata into a column to load a metadata value into a column, use the metadata function in the select sql statement and replace key with the key you want to load you can use transformation functions to achieve the final data type or allow the pipeline to apply automatic casting metadata(key) 149,134,380 true unhandled content type unhandled content type unhandled content type unhandled content type unhandled content type unhandled content type retrieve a value from filename metadata to retrieve a value from a key value pair in the filename metadata, specify the first argument as 'hive partition' and provide a search string for the key in this case, the filename must follow hive naming standards the standard embeds field names and key value pairs in path segments, such as /year=2019/month=2/data parquet if there are duplicate key value pairs in the filename, the function uses the last pair the function returns a string with the value of the associated key, and returns null if the file does not contain the search string or the filename does not follow hive naming standards metadata('hive partition',search string) 149,134,380 true unhandled content type unhandled content type unhandled content type unhandled content type unhandled content type unhandled content type loads a variety of header metadata along with each record of the data pipeline metadata('header', header row index, header col index) 149,134,380 true unhandled content type unhandled content type unhandled content type unhandled content type unhandled content type unhandled content type 1 1 unhandled content type 1 1 unhandled content type 1 1 unhandled content type metadata fields cannot be combined in a transformation function with other source data supported values for the metadata key the metadata values you can load differ based on the source type this table lists the available values for the metadata keys specified using the key argument by source type and their returned data type metadata key values are not case sensitive true 145,145,145,145left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left 1 1 unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type left unhandled content type examples load filename metadata this example snippet uses the create pipeline sql statement to load data and the source filename with each record in a pipeline for details about this pipeline definition and setup, see docid\ stial7oztpmpndfwcsm29 create pipeline orders pipeline source s3 endpoint 'https //s3 us east 1 amazonaws com' bucket 'ocient examples' filter 'metabase samples/csv/orders csv' extract format csv num header lines 1 into public orders select $1 as id, $2 as user id, $3 as product id, $4 as subtotal, $5 as tax, $6 as total, $7 as discount, $8 as created at, $9 as quantity, metadata('filename') as filename column; load hive style partitioned data this example uses the create pipeline sql statement to load data and the value of the search string 'year' of the filename with each record in a pipeline the {{aws}} s3 filter option contains the filter for the year in a file path in turn, the metadata function uses the filter 'year' value to load all records from files with the year 2019 in the specified path for details about this pipeline definition and setup, see docid\ stial7oztpmpndfwcsm29 the example assumes the filename follows hive style naming standards create pipeline orders pipeline source s3 endpoint 'https //s3 us east 1 amazonaws com' bucket 'ocient examples' filter '/year=2019/ ' extract format csv num header lines 1 into public orders select $1 as id, $2 as user id, $3 as product id, $4 as subtotal, $5 as tax, $6 as total, $7 as discount, $8 as created at, $9 as quantity, metadata('hive partition','year') as hive; related links docid\ zncvnrhsf6fg1yvqk6mxt docid\ pbyszqvu5wonpgoso qto docid\ ti3mdibvgmuudmlqu9xpl