Nested - ClickHouse Documentation

Nested(name1 Type1, Name2 Type2, …)

A nested data structure is like a table inside a cell. The parameters of a nested data structure – the column names and types – are specified the same way as in a CREATE TABLE query. Each table row can correspond to any number of rows in a nested data structure.

Avoid using dots in column namesColumn names containing dots, columns sharing a common dot-prefix, and columns with the Array type can each be interpreted as part of a flattened Nested structure when flatten_nested = 1 (the default). This can cause unexpected array-length validation on inserts and renaming restrictions.Avoid using dots in column names if possible. Use underscores (_) or another separator instead of dots in column names unless you intentionally need Nested semantics.

Example:

CREATE TABLE test.visits
(
    CounterID UInt32,
    StartDate Date,
    Sign Int8,
    IsNew UInt8,
    VisitID UInt64,
    UserID UInt64,
    ...
    Goals Nested
    (
        ID UInt32,
        Serial UInt32,
        EventTime DateTime,
        Price Int64,
        OrderID String,
        CurrencyID UInt32
    ),
    ...
) ENGINE = CollapsingMergeTree(StartDate, intHash32(UserID), (CounterID, StartDate, intHash32(UserID), VisitID), 8192, Sign)

This example declares the Goals nested data structure, which contains data about conversions (goals reached). Each row in the ‘visits’ table can correspond to zero or any number of conversions. When flatten_nested is set to 0 (which is not by default), arbitrary levels of nesting are supported. In most cases, when working with a nested data structure, its columns are specified with column names separated by a dot. These columns make up an array of matching types. All the column arrays of a single nested data structure have the same length. Example:

SELECT
    Goals.ID,
    Goals.EventTime
FROM test.visits
WHERE CounterID = 101500 AND length(Goals.ID) < 5
LIMIT 10

┌─Goals.ID───────────────────────┬─Goals.EventTime───────────────────────────────────────────────────────────────────────────┐
│ [1073752,591325,591325]        │ ['2014-03-17 16:38:10','2014-03-17 16:38:48','2014-03-17 16:42:27']                       │
│ [1073752]                      │ ['2014-03-17 00:28:25']                                                                   │
│ [1073752]                      │ ['2014-03-17 10:46:20']                                                                   │
│ [1073752,591325,591325,591325] │ ['2014-03-17 13:59:20','2014-03-17 22:17:55','2014-03-17 22:18:07','2014-03-17 22:18:51'] │
│ []                             │ []                                                                                        │
│ [1073752,591325,591325]        │ ['2014-03-17 11:37:06','2014-03-17 14:07:47','2014-03-17 14:36:21']                       │
│ []                             │ []                                                                                        │
│ []                             │ []                                                                                        │
│ [591325,1073752]               │ ['2014-03-17 00:46:05','2014-03-17 00:46:05']                                             │
│ [1073752,591325,591325,591325] │ ['2014-03-17 13:28:33','2014-03-17 13:30:26','2014-03-17 18:51:21','2014-03-17 18:51:45'] │
└────────────────────────────────┴───────────────────────────────────────────────────────────────────────────────────────────┘

It is easiest to think of a nested data structure as a set of multiple column arrays of the same length. The only place where a SELECT query can specify the name of an entire nested data structure instead of individual columns is the ARRAY JOIN clause. For more information, see “ARRAY JOIN clause”. Example:

SELECT
    Goal.ID,
    Goal.EventTime
FROM test.visits
ARRAY JOIN Goals AS Goal
WHERE CounterID = 101500 AND length(Goals.ID) < 5
LIMIT 10

┌─Goal.ID─┬──────Goal.EventTime─┐
│ 1073752 │ 2014-03-17 16:38:10 │
│  591325 │ 2014-03-17 16:38:48 │
│  591325 │ 2014-03-17 16:42:27 │
│ 1073752 │ 2014-03-17 00:28:25 │
│ 1073752 │ 2014-03-17 10:46:20 │
│ 1073752 │ 2014-03-17 13:59:20 │
│  591325 │ 2014-03-17 22:17:55 │
│  591325 │ 2014-03-17 22:18:07 │
│  591325 │ 2014-03-17 22:18:51 │
│ 1073752 │ 2014-03-17 11:37:06 │
└─────────┴─────────────────────┘

You can’t perform SELECT for an entire nested data structure. You can only explicitly list individual columns that are part of it. For an INSERT query, you should pass all the component column arrays of a nested data structure separately (as if they were individual column arrays). During insertion, the system checks that they have the same length. For a DESCRIBE query, the columns in a nested data structure are listed separately in the same way. The ALTER query for elements in a nested data structure has limitations.

​Nested(name1 Type1, Name2 Type2, …)

Nested(name1 Type1, Name2 Type2, …)