Redshift Spectrum is a feature of Amazon Redshift that allows you to query data stored on Amazon S3 directly and supports nested data types. In this article, we will check how to export redshift data to json format with some examples. I am trying to use the copy command to load a bunch of JSON files on S3 to redshift. When trying to query from Spectrum, however, it returns: Top level Ion/JSON structure must be an anonymous array if and only if serde property 'strip.outer.array' is set. Getting setup with Amazon Redshift Spectrum is quick and easy. The given JSON path can be nested up to five levels. This post discusses which use cases can benefit from nested data types, how to use Amazon Redshift Spectrum with nested data types to achieve excellent performance and storage efficiency, and some of the limitations of nested data types. Customers already have nested data in their Amazon S3 data lake. Amazon Redshift Spectrum supports the following formats AVRO, PARQUET, TEXTFILE, SEQUENCEFILE, RCFILE, RegexSerDe, ORC, Grok, CSV, Ion, and JSON. For example, commonly java applications often use JSON as a standard for data exchange. The first step in configuring the S3 Load component is to provide the Redshift table which the data in the S3 file is to be loaded into. Here is the most recent spectrum-s3.json ... You can also manually enter an IAM role if you don’t see it included the list (for example, if the IAM role hasn’t been created yet). Amazon Redshift Spectrum extends Redshift by offloading data to S3 for querying. “Redshift Spectrum can directly query open file formats in Amazon S3 and data in Redshift in a … Example structure of the JSON file is: { message: 3 time: 1521488151 user: 39283 information: { bytes: 2342343 speed: 9392 location: CA } } You create Redshift Spectrum tables by defining the structure for your files and registering them as tables in an external data catalog. The JSON data I am trying to query has several fields which structure is fixed and expected. The function JSON_EXTRACT_PATH_TEXT returns the value for the key:value pair referenced by a series of path elements in a JSON string. In this example we have a JSON file containing details of different types of donuts sold, a snippet of the file is below: Target Table. Redshift Spectrum also scales intelligently. However, it gets difficult and very time consuming for more complex JSON data such as the one found in the Trello JSON. As a best practice to improve performance and lower costs, Amazon suggests using columnar data formats such as Apache Parquet . This tutorial assumes that you know the basics of S3 and Redshift. I am trying to cast a variable type JSON field in Redshift Spectrum as a plane string but keep getting column type VARCHAR for column STRUCT is incompatible. The JSON format is one of the widely used file formats to store data that you want to transmit to another server. Amazon Redshift Array Support and Alternatives – Example; Redshift JSON_EXTRACT_PATH_TEXT Function. This approach works reasonably well for simple JSON documents. Redshift Spectrum can query data over orc, rc, avro, json,csv, sequencefile, parquet, and textfiles with the support of gzip, bzip2, and snappy compression. Redshift Spectrum does not have the limitations of the native Redshift SQL extensions for JSON. The JSON file format is an alternative to XML. 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