Quick Query

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An Interactive Query Service that Quickly Analyzes Data Stored on Object Storage

Quick Query is an interactive query service that uses standard SQL to analyze large sets of data with ease. Accessing various data sources such as Object Storage, Hadoop, and RDB is easy, and it offers compatibility with various/different standard data formats. MPP(Massively Parallel Processing)-based query engine also ensures fast processing of data.

Overview

  • Fast and Easy Data Query

    When executing a query using standard SQL after defining the schema for data stored on an Object Storage, a fast and easy check of data is achieved. It doesn’t take a professional analyst well-versed in SQL to analyze large data sets.

  • Fast Parallel Processing

    Quick Query uses a Trino engine capable of parallel processing to split query automatically, and query result for large data sets is delivered quickly by performing parallel processing on multiple nodes concurrently.

  • Various Service Structures

    Quick Query provides three modes : Shared dedicated resource mode, shared scalable resource mode and private scalable resource mode. Shared dedicated resource mode ensures reliable response speed for large data query request, whereas shared scalable resource mode offers a more affordable pricing for irregular usage. Private scalable resource mode uses a quick query structure that can support analysis jobs in an independent environment and users can choose the quick query structure they need.

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Service Architecture

  • User → Request/Distribute Products → Quick Query ← Process Data ← Data Engineer
  • Manage Permissions (Apache Ranger) → Quick Query → Save Results → Object Storage
  • Data Source Hooking → Quick Query → Save Results → Object Storage
Quick Query
  • Trino Coordinator
  • Trino Worker
  • Hive Metastore
  • Query Runner
  • Metadata Database
Data Source
  • RDB (PostgreSQL, MariaDB, MS-SQL, MySQL, etc.)
  • Hadoop
  • File
  • Object Storage

Key Features

  • Support various data sources

    - Object Storage, HDFS, Hive, RDB(PostgreSQL, MariaDB, MS-SQL, MySQL, etc.), File

  • Compatible with standard data formats

    - CSV, JSON, ORC, Avro, Parquet, etc.

  • Simple data management

    - Check query history : Query execution results, execution information, query execution history
    - Save and manage query statements entered in Query Editor
    - Users enter/execute query and check/download results

Pricing

    • Billing
    • Charged by the amount of data used by Quick Query
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