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
schema fields
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.
dimensionFieldSpecs
A dimensionFieldSpec is defined for each dimension column. For more details, scroll down to dimensionFieldSpec​
metricFieldSpecs
A metricFieldSpec is defined for each metric column. For more details, scroll down to metricFieldSpec​
dateTimeFieldSpec
A dateTimeFieldSpec is defined for the time columns. There can be multiple time columns. For more details, scroll down to dateTimeFieldSpec.
Below is a detailed description of each type of field spec.
dimensionFieldSpecs
A dimensionFieldSpec is defined for each dimension column. Here's a list of the fields in the dimensionFieldSpec
Property
Description
name
Name of the dimension column
dataType
Data type of the dimension column. Can be STRING, BOOLEAN, INT, LONG, DOUBLE, FLOAT, 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 value or a multi value column. In the example above, the dimension tags is multi-valued. This means that it can have multiple values for a particular row, say tag1, tag2, tag3. For a multi-valued column, individual rows don’t necessarily need to 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. 
Internal default null values for dimension
Data Type
Internal Default Null Value
INT
​Integer.MIN_VALUE​
LONG
​LONG.MIN_VALUE​
FLOAT
​Float.NEGATIVE_INFINITY​
DOUBLE
​DOUBLE.NEGATIVE_INFINITY​
STRING
"null"
BYTES
byte array of length 0
metricFieldSpecs
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, DOUBLE, FLOAT, 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. The values are the same as those used for dimensionFieldSpec.
Internal default null values for metric
Data Type
Internal Default Null Value
INT
0
LONG
0
FLOAT
0.0
DOUBLE
0.0
STRING
"null"
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
name
Name of the date time column
dataType
Data type of the date time column. Can be STRING, INT, LONG
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
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
​

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schema fields	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.
dimensionFieldSpecs	A dimensionFieldSpec is defined for each dimension column. For more details, scroll down to dimensionFieldSpec
metricFieldSpecs	A metricFieldSpec is defined for each metric column. For more details, scroll down to metricFieldSpec
dateTimeFieldSpec	A dateTimeFieldSpec is defined for the time columns. There can be multiple time columns. For more details, scroll down to dateTimeFieldSpec.

Property	Description
name	Name of the dimension column
dataType	Data type of the dimension column. Can be STRING, BOOLEAN, INT, LONG, DOUBLE, FLOAT, 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 value or a multi value column. In the example above, the dimension `tags` is multi-valued. This means that it can have multiple values for a particular row, say `tag1, tag2, tag3`. For a multi-valued column, individual rows don’t necessarily need to 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.`

Data Type	Internal Default Null Value
INT	Integer.MIN_VALUE
LONG	LONG.MIN_VALUE
FLOAT	Float.NEGATIVE_INFINITY
DOUBLE	DOUBLE.NEGATIVE_INFINITY
STRING	"null"
BYTES	byte array of length 0

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