Schema

Schema is used to define the names, data types, and other information for the columns of a Pinot table.

The Pinot schema is composed of:

Field	Description
schemaName	Defines the name of the schema. This is usually the same as the table name. The offline and the realtime table of a hybrid table should use the same schema.
dimensionFieldSpec	A dimensionFieldSpec is defined for each dimension column. For more details, scroll down to .
metricFieldSpec	A metricFieldSpec is defined for each metric column. For more details, scroll down to .
dateTimeFieldSpec	A dateTimeFieldSpec is defined for the time columns. There can be multiple time columns. For more details, scroll down to .

Field

Description

schemaName

Defines the name of the schema. This is usually the same as the table name. The offline and the realtime table of a hybrid table should use the same schema.

dimensionFieldSpec

A dimensionFieldSpec is defined for each dimension column. For more details, scroll down to .

metricFieldSpec

A metricFieldSpec is defined for each metric column. For more details, scroll down to .

dateTimeFieldSpec

A dateTimeFieldSpec is defined for the time columns. There can be multiple time columns. For more details, scroll down to .

Below is a detailed description of each type of field spec.

DimensionFieldSpec

A dimensionFieldSpec is defined for each dimension column. Here's a list of the fields in the dimensionFieldSpec:

Property Description

Property	Description
name	Name of the dimension column.
dataType	Data type of the dimension column. Can be INT, LONG, FLOAT, DOUBLE, BOOLEAN, TIMESTAMP, STRING, BYTES.
defaultNullValue	Represents null values in the data, since Pinot doesn't support storing null column values natively (as part of its on-disk storage format). If not specified, an internal default null value is used as listed here.
singleValueField	Boolean indicating if this is a single-valued or a multi-valued column. Multi-valued column is modeled as a list, where the order of the values are preserved and duplicate values are allowed. Individual rows don’t necessarily have the same number of values. Typical use case for this would be a column such as `skillSet` for a person (one row in the table) that can have multiple values such as `Real Estate, Mortgages`. The default null value for a multi-valued column is a single `defaultNullValue`, e.g. `[Integer.MIN_VALUE]`.

name

Name of the dimension column.

dataType

Data type of the dimension column. Can be INT, LONG, FLOAT, DOUBLE, BOOLEAN, TIMESTAMP, STRING, BYTES.

defaultNullValue

Represents null values in the data, since Pinot doesn't support storing null column values natively (as part of its on-disk storage format). If not specified, an internal default null value is used as listed here.

singleValueField

Boolean indicating if this is a single-valued or a multi-valued column. Multi-valued column is modeled as a list, where the order of the values are preserved and duplicate values are allowed. Individual rows don’t necessarily have the same number of values. Typical use case for this would be a column such as skillSet for a person (one row in the table) that can have multiple values such as Real Estate, Mortgages. The default null value for a multi-valued column is a single defaultNullValue, e.g. [Integer.MIN_VALUE].

Internal default null values for dimension

Data Type Internal Default Null Value

Data Type	Internal Default Null Value
INT
LONG
FLOAT
DOUBLE
BOOLEAN	0 (`false`)
TIMESTAMP	0 (`1970-01-01 00:00:00 UTC`)
STRING	"null"
BYTES	byte array of length 0

INT

LONG

FLOAT

DOUBLE

BOOLEAN

0 (false)

TIMESTAMP

0 (1970-01-01 00:00:00 UTC)

STRING

"null"

BYTES

byte array of length 0

MetricFieldSpec

A metricFieldSpec is defined for each metric column. Here's a list of fields in the metricFieldSpec

Property	Description
name	Name of the metric column
dataType	Data type of the column. Can be INT, LONG, FLOAT, DOUBLE, BYTES (for specialized representations such as HLL, TDigest, etc, where the column stores byte serialized version of the value)
defaultNullValue	Represents null values in the data. If not specified, an internal default null value is used, as listed here.

Property

Description

name

Name of the metric column

dataType

Data type of the column. Can be INT, LONG, FLOAT, DOUBLE, BYTES (for specialized representations such as HLL, TDigest, etc, where the column stores byte serialized version of the value)

defaultNullValue

Represents null values in the data. If not specified, an internal default null value is used, as listed here.

Internal default null values for metric

Data Type	Internal Default Null Value
INT	0
LONG	0
FLOAT	0.0
DOUBLE	0.0
BYTES	byte array of length 0

DateTimeFieldSpec

A dateTimeFieldSpec is used to define time columns of the table. Here's a list of the fields in a dateTimeFieldSpec

Property Description

Property	Description
name	Name of the date time column
dataType	Data type of the date time column. Can be STRING, INT, LONG or TIMESTAMP
format	The format of the time column. The syntax of the format is `timeSize:timeUnit:timeFormat` timeFormat can be either EPOCH or SIMPLE_DATE_FORMAT. If it is SIMPLE_DATE_FORMAT, the pattern string is also specified. For example: 1:MILLISECONDS:EPOCH - epoch millis 1:HOURS:EPOCH - epoch hours 1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd - date specified like `20191018` 1:HOURS:SIMPLE_DATE_FORMAT:EEE MMM dd HH:mm:ss ZZZ yyyy - date specified like `Mon Aug 24 12:36:50 America/Los_Angeles 2019` Noted that if TIMESTAMP type is used in dataType, format is ignored because JDBC standard SQL requires TIMESTAMP in `yyyy-[m]m-[d]d hh:mm:ss[.f...]` format.
granularity	The granularity in which the column is bucketed. The syntax of granularity is `bucket size:bucket unit` For example, the format can be milliseconds `1:MILLISECONDS:EPOCH`, but bucketed to 15 minutes i.e. we only have one value for every 15 minute interval, in which case granularity can be specified as `15:MINUTES`
defaultNullValue	Represents null values in the data. If not specified, an internal default null value is used, as listed here. The values are the same as those used for dimensionFieldSpec.

name

Name of the date time column

dataType

Data type of the date time column. Can be STRING, INT, LONG or TIMESTAMP

format

The format of the time column. The syntax of the format is timeSize:timeUnit:timeFormat

timeFormat can be either EPOCH or SIMPLE_DATE_FORMAT. If it is SIMPLE_DATE_FORMAT, the pattern string is also specified. For example:

1:MILLISECONDS:EPOCH - epoch millis

1:HOURS:EPOCH - epoch hours

1:DAYS:SIMPLE_DATE_FORMAT:yyyyMMdd - date specified like 20191018

1:HOURS:SIMPLE_DATE_FORMAT:EEE MMM dd HH:mm:ss ZZZ yyyy - date specified like Mon Aug 24 12:36:50 America/Los_Angeles 2019

Noted that if TIMESTAMP type is used in dataType, format is ignored because JDBC standard SQL requires TIMESTAMP in yyyy-[m]m-[d]d hh:mm:ss[.f...] format.

granularity

The granularity in which the column is bucketed. The syntax of granularity is bucket size:bucket unit For example, the format can be milliseconds 1:MILLISECONDS:EPOCH, but bucketed to 15 minutes i.e. we only have one value for every 15 minute interval, in which case granularity can be specified as 15:MINUTES

defaultNullValue

Represents null values in the data. If not specified, an internal default null value is used, as listed here. The values are the same as those used for dimensionFieldSpec.

Advanced fields

Apart from these, there's some advanced fields. These are common to all field specs.

Property	Description
maxLength	Max length of this column
virtualColumnProvider	Column value provider

Property

Description

maxLength

Max length of this column

virtualColumnProvider

Column value provider

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Last updated 2 years ago