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:
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.
A dimensionFieldSpec is defined for each dimension column. For more details, scroll down to DimensionFieldSpec.
A metricFieldSpec is defined for each metric column. For more details, scroll down to MetricFieldSpec.
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.
A dimensionFieldSpec is defined for each dimension column. Here's a list of the fields in the dimensionFieldSpec:
Name of the dimension column.
Data type of the dimension column. Can be INT, LONG, FLOAT, DOUBLE, BOOLEAN, TIMESTAMP, STRING, BYTES.
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.
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].
A metricFieldSpec is defined for each metric column. Here's a list of fields in the metricFieldSpec
Name of the metric column
Data type of the column. Can be INT, LONG, FLOAT, DOUBLE, BIG_DECIMAL, BYTES (for specialized representations such as HLL, TDigest, etc, where the column stores byte serialized version of the value)
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
Internal Default Null Value
byte array of length 0
A dateTimeFieldSpec is used to define time columns of the table. Here's a list of the fields in a dateTimeFieldSpec
Name of the date time column
Data type of the date time column. Can be STRING, INT, LONG or TIMESTAMP
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.
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
Represents null values in the data. If not specified, an internal default null value is used. The internal default null value is the same as dimension field.
For the main time column of the table (time column specified in the segmentsConfig
in the table config), the main time column value must be in the range of 1971-01-01 UTC to 2071-01-01 UTC for segment management purpose (e.g. retention, time boundary). If the specified default null value is not within this range, segment creation time is used.
Apart from these, there's some advanced fields. These are common to all field specs.