LogoLogo
release-0.11.0
release-0.11.0
  • Introduction
  • Basics
    • Concepts
    • Architecture
    • Components
      • Cluster
      • Controller
      • Broker
      • Server
      • Minion
      • Tenant
      • Schema
      • Table
      • Segment
      • Deep Store
      • Pinot Data Explorer
    • Getting Started
      • Running Pinot locally
      • Running Pinot in Docker
      • Quick Start Examples
      • Running in Kubernetes
      • Running on public clouds
        • Running on Azure
        • Running on GCP
        • Running on AWS
      • Batch import example
      • Stream ingestion example
      • HDFS as Deep Storage
      • Troubleshooting Pinot
      • Frequently Asked Questions (FAQs)
        • General
        • Pinot On Kubernetes FAQ
        • Ingestion FAQ
        • Query FAQ
        • Operations FAQ
    • Import Data
      • From Query Console
      • Batch Ingestion
        • Spark
        • Hadoop
        • Backfill Data
        • Dimension Table
      • Stream ingestion
        • Apache Kafka
        • Amazon Kinesis
        • Apache Pulsar
      • Stream Ingestion with Upsert
      • Stream Ingestion with Dedup
      • File Systems
        • Amazon S3
        • Azure Data Lake Storage
        • HDFS
        • Google Cloud Storage
      • Input formats
      • Complex Type (Array, Map) Handling
    • Indexing
      • Forward Index
      • Inverted Index
      • Star-Tree Index
      • Bloom Filter
      • Range Index
      • Text search support
      • JSON Index
      • Geospatial
      • Timestamp Index
    • Releases
      • 0.10.0
      • 0.9.3
      • 0.9.2
      • 0.9.1
      • 0.9.0
      • 0.8.0
      • 0.7.1
      • 0.6.0
      • 0.5.0
      • 0.4.0
      • 0.3.0
      • 0.2.0
      • 0.1.0
    • Recipes
      • GitHub Events Stream
  • For Users
    • Query
      • Querying Pinot
      • Aggregation Functions
      • Transformation Functions
      • User-Defined Functions (UDFs)
      • Grouping Algorithm
      • Query Options
      • Cardinality Estimation
      • Lookup UDF Join
      • Querying JSON data
      • Filtering with IdSet
      • Explain Plan
      • GapFill Function For Time-Series Dataset
    • APIs
      • Broker Query API
        • Query Response Format
      • Controller Admin API
    • External Clients
      • JDBC
      • Java
      • Python
      • Golang
    • Tutorials
      • Use OSS as Deep Storage for Pinot
      • Ingest Parquet Files from S3 Using Spark
      • Creating Pinot Segments
      • Use S3 as Deep Storage for Pinot
      • Use S3 and Pinot in Docker
      • Batch Data Ingestion In Practice
      • Schema Evolution
  • For Developers
    • Basics
      • Extending Pinot
        • Writing Custom Aggregation Function
        • Segment Fetchers
      • Contribution Guidelines
      • Code Setup
      • Code Modules and Organization
      • Update Documentation
    • Advanced
      • Data Ingestion Overview
      • Ingestion Aggregations
      • Ingestion Transformations
      • Null Value Support
      • V2 Multi-Stage Query Engine
      • Advanced Pinot Setup
    • Plugins
      • Write Custom Plugins
        • Input Format Plugin
        • Filesystem Plugin
        • Batch Segment Fetcher Plugin
        • Stream Ingestion Plugin
    • Design Documents
      • Segment Writer API
  • For Operators
    • Deployment and Monitoring
      • Setup cluster
      • Server Startup Status Checkers
      • Setup table
      • Setup ingestion
      • Decoupling Controller from the Data Path
      • Segment Assignment
      • Instance Assignment
      • Rebalance
        • Rebalance Servers
        • Rebalance Brokers
      • Tiered Storage
      • Pinot managed Offline flows
      • Minion merge rollup task
      • Access Control
      • Monitoring
      • Tuning
        • Realtime
        • Routing
      • Upgrading Pinot with confidence
    • Command-Line Interface (CLI)
    • Configuration Recommendation Engine
    • Tutorials
      • Authentication, Authorization, and ACLs
      • Configuring TLS/SSL
      • Build Docker Images
      • Running Pinot in Production
      • Kubernetes Deployment
      • Amazon EKS (Kafka)
      • Amazon MSK (Kafka)
      • Monitor Pinot using Prometheus and Grafana
      • Performance Optimization Configurations
  • Configuration Reference
    • Cluster
    • Controller
    • Broker
    • Server
    • Table
    • Schema
    • Ingestion Job Spec
    • Monitoring Metrics
    • Functions
      • ABS
      • ADD
      • arrayConcatDouble
      • arrayConcatFloat
      • arrayConcatInt
      • arrayConcatLong
      • arrayConcatString
      • arrayContainsInt
      • arrayContainsString
      • arrayDistinctInt
      • arrayDistinctString
      • arrayIndexOfInt
      • arrayIndexOfString
      • ARRAYLENGTH
      • arrayRemoveInt
      • arrayRemoveString
      • arrayReverseInt
      • arrayReverseString
      • arraySliceInt
      • arraySliceString
      • arraySortInt
      • arraySortString
      • arrayUnionInt
      • arrayUnionString
      • AVGMV
      • Base64
      • ceil
      • CHR
      • codepoint
      • concat
      • count
      • COUNTMV
      • day
      • dayOfWeek
      • dayOfYear
      • DISTINCT
      • DISTINCTCOUNT
      • DISTINCTCOUNTBITMAP
      • DISTINCTCOUNTBITMAPMV
      • DISTINCTCOUNTHLL
      • DISTINCTCOUNTHLLMV
      • DISTINCTCOUNTMV
      • DISTINCTCOUNTRAWHLL
      • DISTINCTCOUNTRAWHLLMV
      • DISTINCTCOUNTRAWTHETASKETCH
      • DISTINCTCOUNTTHETASKETCH
      • DIV
      • DATETIMECONVERT
      • DATETRUNC
      • exp
      • FLOOR
      • FromDateTime
      • FromEpoch
      • FromEpochBucket
      • Histogram
      • hour
      • JSONFORMAT
      • JSONPATH
      • JSONPATHARRAY
      • JSONPATHARRAYDEFAULTEMPTY
      • JSONPATHDOUBLE
      • JSONPATHLONG
      • JSONPATHSTRING
      • jsonextractkey
      • jsonextractscalar
      • length
      • ln
      • lower
      • lpad
      • ltrim
      • max
      • MAXMV
      • MD5
      • millisecond
      • min
      • minmaxrange
      • MINMAXRANGEMV
      • MINMV
      • minute
      • MOD
      • mode
      • month
      • mult
      • now
      • percentile
      • percentileest
      • percentileestmv
      • percentilemv
      • percentiletdigest
      • percentiletdigestmv
      • quarter
      • regexpExtract
      • regexpReplace
      • remove
      • replace
      • reverse
      • round
      • rpad
      • rtrim
      • second
      • SEGMENTPARTITIONEDDISTINCTCOUNT
      • sha
      • sha256
      • sha512
      • sqrt
      • startswith
      • ST_AsBinary
      • ST_AsText
      • ST_Contains
      • ST_Distance
      • ST_GeogFromText
      • ST_GeogFromWKB
      • ST_GeometryType
      • ST_GeomFromText
      • ST_GeomFromWKB
      • STPOINT
      • ST_Polygon
      • strpos
      • ST_Union
      • SUB
      • substr
      • sum
      • summv
      • TIMECONVERT
      • timezoneHour
      • timezoneMinute
      • ToDateTime
      • ToEpoch
      • ToEpochBucket
      • ToEpochRounded
      • TOJSONMAPSTR
      • toGeometry
      • toSphericalGeography
      • trim
      • upper
      • Url
      • UTF8
      • VALUEIN
      • week
      • year
      • yearOfWeek
  • RESOURCES
    • Community
    • Team
    • Blogs
    • Presentations
    • Videos
  • Integrations
    • Tableau
    • Trino
    • ThirdEye
    • Superset
    • Presto
Powered by GitBook
On this page
  • Signature
  • Usage Examples

Was this helpful?

Edit on GitHub
Export as PDF
  1. Configuration Reference
  2. Functions

DATETRUNC

This section contains reference documentation for the DATETRUNC function.

(Presto) SQL compatible date truncation, equivalent to the Presto function date_trunc.

Converts the value into a specified output granularity seconds since UTC epoch that is bucketed on a unit in a specified timezone.

Signature

DATETRUNC(unit, timeValue)

DATETRUNC(unit, timeValue, inputTimeUnitStr)

DATETRUNC(unit, timeValue, inputTimeUnitStr, timeZone)

DATETRUNC(unit, timeValue, inputTimeUnitStr, timeZone, outputTimeUnitStr)

unit supports the following values:

  • millisecond

  • second

  • minute

  • hour

  • day

  • week

  • month

  • quarter

  • year

inputTimeUnitStr and outputTimeUnitStr support the following values:

  • NANOSECONDS

  • MICROSECONDS

  • MILLISECONDS

  • SECONDS

  • MINUTES

  • HOURS

  • DAYS

Usage Examples

Truncates an epoch in milliseconds at WEEK (where a Week starts at Monday UTC midnight):

select dateTrunc('week', 1639480981746) AS ts
FROM ignoreMe

or

select dateTrunc('week', 1639480981746, 'MILLISECONDS') AS ts
FROM ignoreMe
ts

1639353600000

Truncates an epoch in milliseconds at WEEK (where a Week starts at Monday UTC midnight) in the UTC time zone, returning a result in epoch in seconds in UTC timezone:

select dateTrunc(
  'week', 
  1639480981746, 
  'MILLISECONDS', 
  'UTC', 
  'SECONDS'
) AS ts
FROM ignoreMe
ts

1639353600

Truncates an epoch in milliseconds at WEEK (where a Week starts at Monday UTC midnight) in the CET time zone, returning a result in epoch in seconds in UTC timezone:

select dateTrunc(
  'week', 
  1639480981746, 
  'MILLISECONDS', 
  'CET', 
  'SECONDS'
) AS ts
FROM ignoreMe
ts

1639350000

Truncates an epoch in milliseconds at QUARTER in the Los Angeles time zone (where a Quarter begins on Jan 1st, April 1st, July 1st, October 1st in Los Angeles timezone), returning a result in hours since UTC epoch:

select dateTrunc(
  'quarter', 
  1639480981746, 
  'MILLISECONDS', 
  'America/Los_Angeles', 
  'HOURS'
) AS ts
FROM ignoreMe
ts

453631

PreviousDATETIMECONVERTNextexp

Last updated 2 years ago

Was this helpful?