There are 12 repositories under parquet topic.
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
CSVs sliced, diced & analyzed.
cryo is the easiest way to extract blockchain data to parquet, csv, json, or python dataframes
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
80+ DevOps & Data CLI Tools - AWS, GCP, GCF Python Cloud Functions, Log Anonymizer, Spark, Hadoop, HBase, Hive, Impala, Linux, Docker, Spark Data Converters & Validators (Avro/Parquet/JSON/CSV/INI/XML/YAML), Travis CI, AWS CloudFormation, Elasticsearch, Solr etc.
Simple windows desktop application for viewing & querying Apache Parquet files
Fast data store for Pandas time-series data
Data Preview 🈸 extension for importing 📤 viewing 🔎 slicing 🔪 dicing 🎲 charting 📊 & exporting 📥 large JSON array/config, YAML, Apache Arrow, Avro, Parquet & Excel data files
A tool for batch loading data files (json, parquet, csv, tsv) into ElasticSearch
Python library for fast, interactive geospatial vector data visualization in Jupyter.
Fastest and safest Rust implementation of parquet. `unsafe` free. Integration-tested against pyarrow
fully asynchronous, pure JavaScript implementation of the Parquet file format
A cross-platform (Windows, MAC, Linux) desktop application to view common bigdata binary format like Parquet, ORC, AVRO, etc. Support local file system, HDFS, AWS S3, Azure Blob Storage ,etc.
Go package to read and write parquet files. parquet is a file format to store nested data structures in a flat columnar data format. It can be used in the Hadoop ecosystem and with tools such as Presto and AWS Athena.
Read and write Parquet in Scala. Use Scala classes as schema. No need to start a cluster.
A SQLite vtable extension to read Parquet files
Amazon S3 Find and Forget is a solution to handle data erasure requests from data lakes stored on Amazon S3, for example, pursuant to the European General Data Protection Regulation (GDPR)
Manipulate arrays of complex data structures as easily as Numpy.