Logical types are used to extend the types that parquet can be used to store, by specifying how the primitive types should be interpreted. This keeps the set of primitive types to a minimum and reuses parquet's efficient encodings. For example, strings are stored as byte arrays (binary) with a UTF8 annotation.
This file contains the specification for all logical types.
The parquet format's ConvertedType
stores the type annotation. The annotation may require additional metadata fields, as well as rules for those fields.
UTF8
may only be used to annotate the binary primitive type and indicates that the byte array should be interpreted as a UTF-8 encoded character string.
The sort order used for UTF8
strings is unsigned byte-wise comparison.
ENUM
annotates the binary primitive type and indicates that the value was converted from an enumerated type in another data model (e.g. Thrift, Avro, Protobuf). Applications using a data model lacking a native enum type should interpret ENUM
annotated field as a UTF-8 encoded string.
The sort order used for ENUM
values is unsigned byte-wise comparison.
UUID
annotates a 16-byte fixed-length binary. The value is encoded using big-endian, so that 00112233-4455-6677-8899-aabbccddeeff
is encoded as the bytes 00 11 22 33 44 55 66 77 88 99 aa bb cc dd ee ff
(This example is from wikipedia's UUID page).
The sort order used for UUID
values is unsigned byte-wise comparison.
INT_8
, INT_16
, INT_32
, and INT_64
annotations can be used to specify the maximum number of bits in the stored value. Implementations may use these annotations to produce smaller in-memory representations when reading data.
If a stored value is larger than the maximum allowed by the annotation, the behavior is not defined and can be determined by the implementation. Implementations must not write values that are larger than the annotation allows.
INT_8
, INT_16
, and INT_32
must annotate an int32
primitive type and INT_64
must annotate an int64
primitive type. INT_32
and INT_64
are implied by the int32
and int64
primitive types if no other annotation is present and should be considered optional.
The sort order used for signed integer types is signed.
UINT_8
, UINT_16
, UINT_32
, and UINT_64
annotations can be used to specify unsigned integer types, along with a maximum number of bits in the stored value. Implementations may use these annotations to produce smaller in-memory representations when reading data.
If a stored value is larger than the maximum allowed by the annotation, the behavior is not defined and can be determined by the implementation. Implementations must not write values that are larger than the annotation allows.
UINT_8
, UINT_16
, and UINT_32
must annotate an int32
primitive type and UINT_64
must annotate an int64
primitive type.
The sort order used for unsigned integer types is unsigned.
DECIMAL
annotation represents arbitrary-precision signed decimal numbers of the form unscaledValue * 10^(-scale)
.
The primitive type stores an unscaled integer value. For byte arrays, binary and fixed, the unscaled number must be encoded as two's complement using big-endian byte order (the most significant byte is the zeroth element). The scale stores the number of digits of that value that are to the right of the decimal point, and the precision stores the maximum number of digits supported in the unscaled value.
If not specified, the scale is 0. Scale must be zero or a positive integer less than the precision. Precision is required and must be a non-zero positive integer. A precision too large for the underlying type (see below) is an error.
DECIMAL
can be used to annotate the following types:
int32
: for 1 <= precision <= 9int64
: for 1 <= precision <= 18; precision < 10 will produce a warningfixed_len_byte_array
: precision is limited by the array size. Length n
can store <= floor(log_10(2^(8*n - 1) - 1))
base-10 digitsbinary
: precision
is not limited, but is required. The minimum number of bytes to store the unscaled value should be used.A SchemaElement
with the DECIMAL
ConvertedType
must also have both scale
and precision
fields set, even if scale is 0 by default.
The sort order used for DECIMAL
values is signed comparison of the represented value.
If the column uses int32
or int64
physical types, then signed comparison of the integer values produces the correct ordering. If the physical type is fixed, then the correct ordering can be produced by flipping the most-significant bit in the first byte and then using unsigned byte-wise comparison.
DATE
is used to for a logical date type, without a time of day. It must annotate an int32
that stores the number of days from the Unix epoch, 1 January 1970.
The sort order used for DATE
is signed.
TIME_MILLIS
is used for a logical time type with millisecond precision, without a date. It must annotate an int32
that stores the number of milliseconds after midnight.
The sort order used for TIME\_MILLIS
is signed.
TIME_MICROS
is used for a logical time type with microsecond precision, without a date. It must annotate an int64
that stores the number of microseconds after midnight.
The sort order used for TIME\_MICROS
is signed.
TIMESTAMP_MILLIS
is used for a combined logical date and time type, with millisecond precision. It must annotate an int64
that stores the number of milliseconds from the Unix epoch, 00:00:00.000 on 1 January 1970, UTC.
The sort order used for TIMESTAMP\_MILLIS
is signed.
TIMESTAMP_MICROS
is used for a combined logical date and time type with microsecond precision. It must annotate an int64
that stores the number of microseconds from the Unix epoch, 00:00:00.000000 on 1 January 1970, UTC.
The sort order used for TIMESTAMP\_MICROS
is signed.
INTERVAL
is used for an interval of time. It must annotate a fixed_len_byte_array
of length 12. This array stores three little-endian unsigned integers that represent durations at different granularities of time. The first stores a number in months, the second stores a number in days, and the third stores a number in milliseconds. This representation is independent of any particular timezone or date.
Each component in this representation is independent of the others. For example, there is no requirement that a large number of days should be expressed as a mix of months and days because there is not a constant conversion from days to months.
The sort order used for INTERVAL
is unsigned, produced by sorting by the value of months, then days, then milliseconds with unsigned comparison.
Embedded types do not have type-specific orderings.
JSON
is used for an embedded JSON document. It must annotate a binary
primitive type. The binary
data is interpreted as a UTF-8 encoded character string of valid JSON as defined by the JSON specification
The sort order used for JSON
is unsigned byte-wise comparison.
BSON
is used for an embedded BSON document. It must annotate a binary
primitive type. The binary
data is interpreted as an encoded BSON document as defined by the BSON specification.
The sort order used for BSON
is unsigned byte-wise comparison.
This section specifies how LIST
and MAP
can be used to encode nested types by adding group levels around repeated fields that are not present in the data.
This does not affect repeated fields that are not annotated: A repeated field that is neither contained by a LIST
- or MAP
-annotated group nor annotated by LIST
or MAP
should be interpreted as a required list of required elements where the element type is the type of the field.
Implementations should use either LIST
and MAP
annotations or unannotated repeated fields, but not both. When using the annotations, no unannotated repeated types are allowed.
LIST
is used to annotate types that should be interpreted as lists.
LIST
must always annotate a 3-level structure:
<list-repetition> group <name> (LIST) { repeated group list { <element-repetition> <element-type> element; } }
LIST
that contains a single field named list
. The repetition of this level must be either optional
or required
and determines whether the list is nullable.list
, must be a repeated group with a single field named element
.element
field encodes the list's element type and repetition. Element repetition must be required
or optional
.The following examples demonstrate two of the possible lists of string values.
// List<String> (list non-null, elements nullable) required group my_list (LIST) { repeated group list { optional binary element (UTF8); } } // List<String> (list nullable, elements non-null) optional group my_list (LIST) { repeated group list { required binary element (UTF8); } }
Element types can be nested structures. For example, a list of lists:
// List<List<Integer>> optional group array_of_arrays (LIST) { repeated group list { required group element (LIST) { repeated group list { required int32 element; } } } }
It is required that the repeated group of elements is named list
and that its element field is named element
. However, these names may not be used in existing data and should not be enforced as errors when reading. For example, the following field schema should produce a nullable list of non-null strings, even though the repeated group is named element
.
optional group my_list (LIST) { repeated group element { required binary str (UTF8); }; }
Some existing data does not include the inner element layer. For backward-compatibility, the type of elements in LIST
-annotated structures should always be determined by the following rules:
array
or uses the LIST
-annotated group's name with _tuple
appended then the repeated type is the element type and elements are required.Examples that can be interpreted using these rules:
// List<Integer> (nullable list, non-null elements) optional group my_list (LIST) { repeated int32 element; } // List<Tuple<String, Integer>> (nullable list, non-null elements) optional group my_list (LIST) { repeated group element { required binary str (UTF8); required int32 num; }; } // List<OneTuple<String>> (nullable list, non-null elements) optional group my_list (LIST) { repeated group array { required binary str (UTF8); }; } // List<OneTuple<String>> (nullable list, non-null elements) optional group my_list (LIST) { repeated group my_list_tuple { required binary str (UTF8); }; }
MAP
is used to annotate types that should be interpreted as a map from keys to values. MAP
must annotate a 3-level structure:
<map-repetition> group <name> (MAP) { repeated group key_value { required <key-type> key; <value-repetition> <value-type> value; } }
MAP
that contains a single field named key_value
. The repetition of this level must be either optional
or required
and determines whether the list is nullable.key_value
, must be a repeated group with a key
field for map keys and, optionally, a value
field for map values.key
field encodes the map's key type. This field must have repetition required
and must always be present.value
field encodes the map's value type and repetition. This field can be required
, optional
, or omitted.The following example demonstrates the type for a non-null map from strings to nullable integers:
// Map<String, Integer> required group my_map (MAP) { repeated group key_value { required binary key (UTF8); optional int32 value; } }
If there are multiple key-value pairs for the same key, then the final value for that key must be the last value. Other values may be ignored or may be added with replacement to the map container in the order that they are encoded. The MAP
annotation should not be used to encode multi-maps using duplicate keys.
It is required that the repeated group of key-value pairs is named key_value
and that its fields are named key
and value
. However, these names may not be used in existing data and should not be enforced as errors when reading.
Some existing data incorrectly used MAP_KEY_VALUE
in place of MAP
. For backward-compatibility, a group annotated with MAP_KEY_VALUE
that is not contained by a MAP
-annotated group should be handled as a MAP
-annotated group.
Examples that can be interpreted using these rules:
// Map<String, Integer> (nullable map, non-null values) optional group my_map (MAP) { repeated group map { required binary str (UTF8); required int32 num; } } // Map<String, Integer> (nullable map, nullable values) optional group my_map (MAP_KEY_VALUE) { repeated group map { required binary key (UTF8); optional int32 value; } }
Sometimes when discovering the schema of existing data values are always null and there's no type information. The NULL
type can be used to annotates a column that is always null. (Similar to Null type in Avro)