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Redshift sortkey3/17/2023 The warehouse connector stringifies all context fields that contain a nested array.The warehouse connector stringifies all properties that contain a nested array.To preserve the quality of your events data, Segment uses the following methods to store properties and traits in database tables: Segment’s libraries pass nested objects and arrays into tracking calls as properties, traits, and tracking calls. How warehouse tables handle nested objects and arrays Instead of recording events like “Ordered Product 15”, use a single property of “Product Number” or similar. Segment does not allow unbounded event or property spaces in your data. Will only work when mode = upsert.Ĭolumn_names ( List, optional) – List of column names to map source data fields to the target columns.Note: Segment creates tables for each of your custom events in your warehouse, with columns for each event’s custom properties. Precombine_key ( str, optional) – When there is a primary_key match during upsert, this column will change the upsert method,Ĭomparing the values of the specified column from source and target, and keeping the Varchar_lengths ( Dict, optional) – Dict of VARCHAR length by columns. Varchar_lengths_default ( int) – The size that will be set for all VARCHAR columns not specified with varchar_lengths. Primary_keys ( List, optional) – Primary keys. Sortkey ( List, optional) – List of columns to be sorted. Sortstyle ( str) – Sorting can be “COMPOUND” or “INTERLEAVED”. ĭistkey ( str, optional) – Specifies a column name or positional number for the distribution key. Slow relative to the other methods.ĭiststyle ( str) – Redshift distribution styles. Transaction & starts a new one, hence the overwrite happens in two transactions and is not atomic. truncates the table, but immediately commits current CASCADE - drops the table, and all views that depend on it. Fails if there are any views that depend on it. Mode ( str) – Append, overwrite or upsert.ĭrop, cascade, truncate, or delete. Parquet_infer_sampling ( float) – Random sample ratio of files that will have the metadata inspected. This is only needed when you are using temporary credentials. Iam_role ( str, optional) – AWS IAM role with the related permissions.Īws_access_key_id ( str, optional) – The access key for your AWS account.Īws_secret_access_key ( str, optional) – The secret key for your AWS account.Īws_session_token ( str, optional) – The session key for your AWS account. “credentials directly or wr.nnect() to fetch it from the Glue Catalog. s3://bucket/prefix/)Ĭon ( redshift_connector.Connection) – Use redshift_nnect() to use ” That will be spawned will be gotten from os.cpu_count(). In case of use_threads=True the number of threads Load Parquet files from S3 to a Table on Amazon Redshift (Through COPY command). copy_from_files ( path : str, con : Connection, table : str, schema : str, iam_role : Optional = None, aws_access_key_id : Optional = None, aws_secret_access_key : Optional = None, aws_session_token : Optional = None, parquet_infer_sampling : float = 1.0, mode : str = 'append', overwrite_method : str = 'drop', diststyle : str = 'AUTO', distkey : Optional = None, sortstyle : str = 'COMPOUND', sortkey : Optional ] = None, primary_keys : Optional ] = None, varchar_lengths_default : int = 256, varchar_lengths : Optional ] = None, serialize_to_json : bool = False, path_suffix : Optional = None, path_ignore_suffix : Optional = None, use_threads : Union = True, lock : bool = False, commit_transaction : bool = True, manifest : Optional = False, sql_copy_extra_params : Optional ] = None, boto3_session : Optional = None, s3_additional_kwargs : Optional ] = None, precombine_key : Optional = None, column_names : Optional ] = None ) → None ¶
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