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^ The primary format is binary, but text and JSON formats are available. [8] [9] ^ Means that generic tools/libraries know how to encode, decode, and dereference a reference to another piece of data in the same document. A tool may require the IDL file, but no more. Excludes custom, non-standardized referencing techniques.
Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
JSON (JavaScript Object Notation, pronounced / ˈ dʒ eɪ s ən / or / ˈ dʒ eɪ ˌ s ɒ n /) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of name–value pairs and arrays (or other serializable values).
FlatBuffers is a free software library implementing a serialization format similar to Protocol Buffers, Thrift, Apache Avro, SBE, and Cap'n Proto, primarily written by Wouter van Oortmerssen and open-sourced by Google. It supports “zero-copy” deserialization, so that accessing the serialized data does not require first copying it into a ...
Noggit Solr's streaming JSON parser for Java; Yajl – Yet Another JSON Library. YAJL is a small event-driven (SAX-style) JSON parser written in ANSI C, and a small validating JSON generator. ArduinoJson is a C++ library that supports concatenated JSON. GSON JsonStreamParser.java can read concatenated JSON. json-stream is a streaming JSON ...
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...
Pandas is built around data structures called Series and DataFrames.Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel.