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<!DOCTYPE concept PUBLIC "-//OASIS//DTD DITA Concept//EN" "concept.dtd">
  <concept id="map">

    <title>MAP Complex Type (<keyword keyref="impala23"/> or higher only)</title>

    <prolog>
      <metadata>
        <data name="Category" value="Impala"/>
        <data name="Category" value="Impala Data Types"/>
        <data name="Category" value="SQL"/>
        <data name="Category" value="Developers"/>
        <data name="Category" value="Data Analysts"/>
      </metadata>
    </prolog>

    <conbody>

      <p>
        A complex data type representing an arbitrary set of key-value pairs.
        The key part is a scalar type, while the value part can be a scalar or
        another complex type (<codeph>ARRAY</codeph>, <codeph>STRUCT</codeph>,
        or <codeph>MAP</codeph>).
      </p>

      <p conref="../shared/impala_common.xml#common/syntax_blurb"/>

<codeblock><varname>column_name</varname> MAP &lt; <varname>primitive_type</varname>, <varname>type</varname> &gt;

type ::= <varname>primitive_type</varname> | <varname>complex_type</varname>
</codeblock>

      <p conref="../shared/impala_common.xml#common/usage_notes_blurb"/>

      <p conref="../shared/impala_common.xml#common/complex_types_combo"/>

      <p>
        The <codeph>MAP</codeph> complex data type represents a set of key-value pairs.
        Each element of the map is indexed by a primitive type such as <codeph>BIGINT</codeph> or
        <codeph>STRING</codeph>, letting you define sequences that are not continuous or categories with arbitrary names.
        You might find it convenient for modelling data produced in other languages, such as a
        Python dictionary or Java HashMap, where a single scalar value serves as the lookup key.
      </p>

      <p>
        In a big data context, the keys in a map column might represent a numeric sequence of events during a
        manufacturing process, or <codeph>TIMESTAMP</codeph> values corresponding to sensor observations.
        The map itself is inherently unordered, so you choose whether to make the key values significant
        (such as a recorded <codeph>TIMESTAMP</codeph>) or synthetic (such as a random global universal ID).
      </p>

      <note>
        Behind the scenes, the <codeph>MAP</codeph> type is implemented in a similar way as the
        <codeph>ARRAY</codeph> type. Impala does not enforce any uniqueness constraint on the
        <codeph>KEY</codeph> values, and the <codeph>KEY</codeph> values are processed by
        looping through the elements of the <codeph>MAP</codeph> rather than by a constant-time lookup.
        Therefore, this type is primarily for ease of understanding when importing data and
        algorithms from non-SQL contexts, rather than optimizing the performance of key lookups.
      </note>

      <p conref="../shared/impala_common.xml#common/complex_types_describe"/>

      <p conref="../shared/impala_common.xml#common/added_in_230"/>

      <p conref="../shared/impala_common.xml#common/restrictions_blurb"/>

      <ul conref="../shared/impala_common.xml#common/complex_types_restrictions">
        <li/>
      </ul>

      <p conref="../shared/impala_common.xml#common/kudu_blurb"/>
      <p conref="../shared/impala_common.xml#common/kudu_unsupported_data_type"/>

      <p conref="../shared/impala_common.xml#common/example_blurb"/>

      <note conref="../shared/impala_common.xml#common/complex_type_schema_pointer"/>

      <p>
        The following example shows a table with various kinds of <codeph>MAP</codeph> columns,
        both at the top level and nested within other complex types.
        Each row represents information about a specific country, with complex type fields
        of various levels of nesting to represent different information associated
        with the country: factual measurements such as area and population,
        notable people in different categories, geographic features such as
        cities, points of interest within each city, and mountains with associated facts.
        Practice the <codeph>CREATE TABLE</codeph> and query notation for complex type columns
        using empty tables, until you can visualize a complex data structure and construct corresponding SQL statements reliably.
      </p>

<codeblock><![CDATA[create TABLE map_demo
(
  country_id BIGINT,

-- Numeric facts about each country, looked up by name.
-- For example, 'Area':1000, 'Population':999999.
-- Using a MAP instead of a STRUCT because there could be
-- a different set of facts for each country.
  metrics MAP <STRING, BIGINT>,

-- MAP whose value part is an ARRAY.
-- For example, the key 'Famous Politicians' could represent an array of 10 elements,
-- while the key 'Famous Actors' could represent an array of 20 elements.
  notables MAP <STRING, ARRAY <STRING>>,

-- MAP that is a field within a STRUCT.
-- (The STRUCT is inside another ARRAY, because it is rare
-- for a STRUCT to be a top-level column.)
-- For example, city #1 might have points of interest with key 'Zoo',
-- representing an array of 3 different zoos.
-- City #2 might have completely different kinds of points of interest.
-- Because the set of field names is potentially large, and most entries could be blank,
-- a MAP makes more sense than a STRUCT to represent such a sparse data structure.
  cities ARRAY < STRUCT <
    name: STRING,
    points_of_interest: MAP <STRING, ARRAY <STRING>>
  >>,

-- MAP that is an element within an ARRAY. The MAP is inside a STRUCT field to associate
-- the mountain name with all the facts about the mountain.
-- The "key" of the map (the first STRING field) represents the name of some fact whose value
-- can be expressed as an integer, such as 'Height', 'Year First Climbed', and so on.
  mountains ARRAY < STRUCT < name: STRING, facts: MAP <STRING, INT > > >
)
STORED AS PARQUET;
]]>
</codeblock>

<codeblock><![CDATA[DESCRIBE map_demo;
+------------+------------------------------------------------+
| name       | type                                           |
+------------+------------------------------------------------+
| country_id | bigint                                         |
| metrics    | map<string,bigint>                             |
| notables   | map<string,array<string>>                      |
| cities     | array<struct<                                  |
|            |   name:string,                                 |
|            |   points_of_interest:map<string,array<string>> |
|            | >>                                             |
| mountains  | array<struct<                                  |
|            |   name:string,                                 |
|            |   facts:map<string,int>                        |
|            | >>                                             |
+------------+------------------------------------------------+

DESCRIBE map_demo.metrics;
+-------+--------+
| name  | type   |
+-------+--------+
| key   | string |
| value | bigint |
+-------+--------+

DESCRIBE map_demo.notables;
+-------+---------------+
| name  | type          |
+-------+---------------+
| key   | string        |
| value | array<string> |
+-------+---------------+

DESCRIBE map_demo.notables.value;
+------+--------+
| name | type   |
+------+--------+
| item | string |
| pos  | bigint |
+------+--------+

DESCRIBE map_demo.cities;
+------+------------------------------------------------+
| name | type                                           |
+------+------------------------------------------------+
| item | struct<                                        |
|      |   name:string,                                 |
|      |   points_of_interest:map<string,array<string>> |
|      | >                                              |
| pos  | bigint                                         |
+------+------------------------------------------------+

DESCRIBE map_demo.cities.item.points_of_interest;
+-------+---------------+
| name  | type          |
+-------+---------------+
| key   | string        |
| value | array<string> |
+-------+---------------+

DESCRIBE map_demo.cities.item.points_of_interest.value;
+------+--------+
| name | type   |
+------+--------+
| item | string |
| pos  | bigint |
+------+--------+

DESCRIBE map_demo.mountains;
+------+-------------------------+
| name | type                    |
+------+-------------------------+
| item | struct<                 |
|      |   name:string,          |
|      |   facts:map<string,int> |
|      | >                       |
| pos  | bigint                  |
+------+-------------------------+

DESCRIBE map_demo.mountains.item.facts;
+-------+--------+
| name  | type   |
+-------+--------+
| key   | string |
| value | int    |
+-------+--------+
]]>
</codeblock>

      <p>
        The following example shows a table that uses a variety of data types for the <codeph>MAP</codeph>
        <q>key</q> field. Typically, you use <codeph>BIGINT</codeph> or <codeph>STRING</codeph> to use
        numeric or character-based keys without worrying about exceeding any size or length constraints.
      </p>

<codeblock><![CDATA[CREATE TABLE map_demo_obscure
(
  id BIGINT,
  m1 MAP <INT, INT>,
  m2 MAP <SMALLINT, INT>,
  m3 MAP <TINYINT, INT>,
  m4 MAP <TIMESTAMP, INT>,
  m5 MAP <BOOLEAN, INT>,
  m6 MAP <CHAR(5), INT>,
  m7 MAP <VARCHAR(25), INT>,
  m8 MAP <FLOAT, INT>,
  m9 MAP <DOUBLE, INT>,
  m10 MAP <DECIMAL(12,2), INT>
)
STORED AS PARQUET;
]]>
</codeblock>

<codeblock>CREATE TABLE celebrities (name STRING, birth_year MAP &lt; STRING, SMALLINT &gt;) STORED AS PARQUET;
-- A typical row might represent values with 2 different birth years, such as:
-- ("Joe Movie Star", { "real": 1972, "claimed": 1977 })

CREATE TABLE countries (name STRING, famous_leaders MAP &lt; INT, STRING &gt;) STORED AS PARQUET;
-- A typical row might represent values with different leaders, with key values corresponding to their numeric sequence, such as:
-- ("United States", { 1: "George Washington", 3: "Thomas Jefferson", 16: "Abraham Lincoln" })

CREATE TABLE airlines (name STRING, special_meals MAP &lt; STRING, MAP &lt; STRING, STRING &gt; &gt;) STORED AS PARQUET;
-- A typical row might represent values with multiple kinds of meals, each with several components:
-- ("Elegant Airlines",
--   {
--     "vegetarian": { "breakfast": "pancakes", "snack": "cookies", "dinner": "rice pilaf" },
--     "gluten free": { "breakfast": "oatmeal", "snack": "fruit", "dinner": "chicken" }
--   } )
</codeblock>

      <p conref="../shared/impala_common.xml#common/related_info"/>

      <p>
        <xref href="impala_complex_types.xml#complex_types"/>,
        <xref href="impala_array.xml#array"/>,
        <xref href="impala_struct.xml#struct"/>
        <!-- <xref href="impala_map.xml#map"/> -->
      </p>

    </conbody>

  </concept>