Avro logical types

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Asked 3 years, 6 months ago. Active 1 year, 5 months ago. Viewed 12k times. Active Oldest Votes. In which package i can find LogicalTypes? It's in the standard Avro library at Maven Coordinates "org. Edmond Wong Edmond Wong 71 3 3 bronze badges. LONG ; fields. Field "timestamp", LogicalTypes. DontPanic DontPanic 1, 1 1 gold badge 12 12 silver badges 19 19 bronze badges. Your code works. I posted this in a separate answer. Thank you! Sign up or log in Sign up using Google.

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Related This document defines Apache Avro. It is intended to be the authoritative specification. Implementations of Avro must adhere to this document.

Primitive type names are also defined type names. Thus, for example, the schema "string" is equivalent to:.

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Avro supports six kinds of complex types: records, enums, arrays, maps, unions and fixed. Arrays use the type name "array" and support a single attribute:.

Unions, as mentioned above, are represented using JSON arrays. For example, ["null", "string"] declares a schema which may be either a null or string. Note that when a default value is specified for a record field whose type is a union, the type of the default value must match the first element of the union. Thus, for unions containing "null", the "null" is usually listed first, since the default value of such unions is typically null.

Unions may not contain more than one schema with the same type, except for the named types record, fixed and enum. For example, unions containing two array types or two map types are not permitted, but two types with different names are permitted.

Names permit efficient resolution when reading and writing unions. Fixed uses the type name "fixed" and supports two attributes:. Record, enums and fixed are named types.

avro logical types

Each has a fullname that is composed of two parts; a name and a namespace. Equality of names is defined on the fullname. A namespace is a dot-separated sequence of such names. The empty string may also be used as a namespace to indicate the null namespace. Equality of names including field names and enum symbols as well as fullnames is case-sensitive. The null namespace may not be used in a dot-separated sequence of names.

So the grammar for a namespace is:. In record, enum and fixed definitions, the fullname is determined in one of the following ways:.

References to previously defined names are as in the latter two cases above: if they contain a dot they are a fullname, if they do not contain a dot, the namespace is the namespace of the enclosing definition.

A schema or protocol may not contain multiple definitions of a fullname. Further, a name must be defined before it is used "before" in the depth-first, left-to-right traversal of the JSON parse tree, where the types attribute of a protocol is always deemed to come "before" the messages attribute.

Named types and fields may have aliases. An implementation may optionally use aliases to map a writer's schema to the reader's. This faciliates both schema evolution as well as processing disparate datasets. Aliases function by re-writing the writer's schema using aliases from the reader's schema. For example, if the writer's schema was named "Foo" and the reader's schema is named "Bar" and has an alias of "Foo", then the implementation would act as though "Foo" were named "Bar" when reading.

Similarly, if data was written as a record with a field named "x" and is read as a record with a field named "y" with alias "x", then the implementation would act as though "x" were named "y" when reading. A type alias may be specified either as a fully namespace-qualified, or relative to the namespace of the name it is an alias for. For example, if a type named "a.

Binary encoded Avro data does not include type information or field names.This document defines Apache Avro. It is intended to be the authoritative specification.

Implementations of Avro must adhere to this document. Primitive type names are also defined type names. Thus, for example, the schema "string" is equivalent to:. Avro supports six kinds of complex types: records, enums, arrays, maps, unions and fixed. Arrays use the type name "array" and support a single attribute:. Unions, as mentioned above, are represented using JSON arrays.

For example, ["null", "string"] declares a schema which may be either a null or string. Note that when a default value is specified for a record field whose type is a union, the type of the default value must match the first element of the union.

Thus, for unions containing "null", the "null" is usually listed first, since the default value of such unions is typically null. Unions may not contain more than one schema with the same type, except for the named types record, fixed and enum. For example, unions containing two array types or two map types are not permitted, but two types with different names are permitted.

Names permit efficient resolution when reading and writing unions. Fixed uses the type name "fixed" and supports two attributes:.

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Record, enums and fixed are named types. Each has a fullname that is composed of two parts; a name and a namespace. Equality of names is defined on the fullname. A namespace is a dot-separated sequence of such names. The empty string may also be used as a namespace to indicate the null namespace. Equality of names including field names and enum symbols as well as fullnames is case-sensitive. In record, enum and fixed definitions, the fullname is determined in one of the following ways:.Send us feedback.

Apache Avro is a data serialization system.

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Avro provides:. The Avro data source supports:. Also see Read and write streaming Avro data. To ignore files without the. The default is false. You can set these properties in the cluster Spark configuration or at runtime using spark. For example:. This library supports reading all Avro types. The Avro data source supports reading union types.

Avro considers the following three types to be union types:. All other union types are complex types.

Avro Data Types

They map to StructType where field names are member0member1and so on, in accordance with members of the union. This is consistent with the behavior when converting between Avro and Parquet.

The Avro data source supports reading the following Avro logical types :. The Avro data source ignores docs, aliases, and other properties present in the Avro file. For most types, the mapping from Spark types to Avro types is straightforward for example IntegerType gets converted to int ; the following is a list of the few special cases:. You can also specify the whole output Avro schema with the option avroSchemaso that Spark SQL types can be converted into other Avro types.

The following conversions are not applied by default and require user specified Avro schema:. These examples use the episodes. To query Avro data in SQL, register the data file as a table or temporary view:. Updated Oct 08, Send us feedback. Documentation Data Data sources Avro file. Avro file Apache Avro is a data serialization system.

Avro provides: Rich data structures. A compact, fast, binary data format. A container file, to store persistent data. Remote procedure call RPC. Simple integration with dynamic languages. Code generation is not required to read or write data files nor to use or implement RPC protocols. Code generation as an optional optimization, only worth implementing for statically typed languages.

Partitioning: Easily reading and writing partitioned data without any extra configuration. Compression: Compression to use when writing Avro out to disk. The supported types are uncompressedsnappyand deflate. You can also specify the deflate level.This name is set as the Schema property "logicalType".

The "logicalType" property will be set to this type's name, and other type-specific properties may be added. The Schema is first validated to ensure it is compatible. This will throw an exception if the Schema is incompatible with this type. For example, a date is stored as an int and is incompatible with a fixed Schema.

All rights reserved. Skip navigation links. Object org. DateLogicalTypes. DecimalLogicalTypes. LocalTimestampMicrosLogicalTypes. LocalTimestampMillisLogicalTypes. TimeMicrosLogicalTypes.

TimeMillisLogicalTypes. TimestampMicrosLogicalTypes. Logical types specify a way of representing a high-level type as a base Avro type. For example, a date is specified as the number of days after the unix epoch or before using a negative value. This enables extensions to Avro's type system without breaking binary compatibility.

avro logical types

Older versions see the base type and ignore the logical type. Add this logical type to the given Schema. Validate this logical type for the given Schema.Avro is used to define the data schema for a record's value.

This schema describes the fields allowed in the value, along with their data types. These bindings are used to serialize values before writing them, and to deserialize values after reading them. The usage of these bindings requires your applications to use the Avro data format, which means that each stored value is associated with a schema. The use of Avro schemas allows serialized values to be stored in a very space-efficient binary format.

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Each value is stored without any metadata other than a small internal schema identifier, between 1 and 4 bytes in size. One such reference is stored per key-value pair. In this way, the serialized Avro data format is always associated with the schema used to serialize it, with minimal overhead. This association is made transparently to the application, and the internal schema identifier is managed by the bindings supplied by the AvroCatalog class.

The application never sees or uses the internal identifier directly. JSON is short for JavaScript Object Notationand it is a lightweight, text-based data interchange format that is intended to be easy for humans to read and write. JSON is described in a great many places, both on the web and in after-market documentation.

The above example is a JSON record which describes schema that might be used by the value portion of a key-value pair in the store. It describes a schema for a person's full name. Identifies the JSON field type. For Avro schemas, this must always be record when it is specified at the schema's top level. The type record means that there will be multiple fields defined. This identifies the namespace in which the object lives.

Essentially, this is meant to be a URI that has meaning to you and your organization.

avro logical types

It is used to differentiate one schema type from another should they share the same name. This is the schema name which, when combined with the namespace, uniquely identifies the schema within the store. In the above example, the fully qualified name for the schema is com. This is the actual schema definition.

It defines what fields are contained in the value, and the data type for each field. A field can be a simple data type, such as an integer or a string, or it can be complex data.Avro, being a schema-based serialization utility, accepts schemas as input. In spite of various schemas being available, Avro follows its own standards of defining schemas. Using these schemas, you can store serialized values in binary format using less space.

These values are stored without any metadata. In case of document, it shows the type of the document, generally a record because there are multiple fields. In case of document, it describes the schema name. This schema name together with the namespace, uniquely identifies the schema within the store Namespace. In the above example, the full name of the schema will be Tutorialspoint.

Avro schema is having primitive data types as well as complex data types. A record data type in Avro is a collection of multiple attributes.

This data type defines an array field having a single attribute items. This items attribute specifies the type of items in the array. The map data type is an array of key-value pairs, it organizes data as key-value pairs.

The key for an Avro map must be a string. The values of a map hold the data type of the content of map. A union datatype is used whenever the field has one or more datatypes. They are represented as JSON arrays. For example, if a field that could be either an int or null, then the union is represented as ["int", "null"].

This data type is used to declare a fixed-sized field that can be used for storing binary data. It has field name and data as attributes. Name holds the name of the field, and size holds the size of the field.

Apache Avro™ 1.10.0 Specification

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