How to Query Spark SQL DataFrames with Nested Data Structures (Maps, Arrays, Structs)?

Use Spark SQL to query complex type data frames

Introduction

Spark SQL supports querying complex types stored in data frames, such as maps and arrays. This guide outlines the syntax and methods for accessing and manipulating nested data structures.

Access array

Column.getItem method

<code>df.select($"arrayColumn".getItem(index)).show</code>

Where, index represents the position of the required element in the array.

Hive square bracket syntax

<code>sqlContext.sql("SELECT arrayColumn[index] FROM df").show</code>

User Defined Function (UDF)

<code>val get_ith = udf((xs: Seq[Int], i: Int) => Try(xs(i)).toOption)

df.select(get_ith($"arrayColumn", lit(index))).show</code>

Filtering and transforming arrays

Spark 2.4 introduces built-in functions such as filter, transform, aggregate, and array_* functions that can be used to operate on arrays:

filter

<code>df.selectExpr("filter(arrayColumn, x -> x % 2 == 0) arrayColumn_even").show</code>

transform

<code>df.selectExpr("transform(arrayColumn, x -> x + 1) arrayColumn_inc").show</code>

aggregate

<code>df.selectExpr("aggregate(arrayColumn, 0, (acc, x) -> acc + x, acc -> acc) arrayColumn_sum").show</code>

Other array functions

• array_distinct
• array_max
• flatten
• arrays_zip
• array_union
• slice

Access Mapping

Column.getField method

<code>df.select($"mapColumn".getField("key")).show</code>

Where key represents the name of the required key in the map.

Hive square bracket syntax

<code>sqlContext.sql("SELECT mapColumn['key'] FROM df").show</code>

Full path point syntax

<code>df.select($"mapColumn.key").show</code>

User Defined Function (UDF)

<code>val get_field = udf((kvs: Map[String, String], k: String) => kvs.get(k))

df.select(get_field($"mapColumn", lit("key"))).show</code>

map_* functions

• map_keys
• map_values

Access structure

Full path point syntax

<code>df.select($"structColumn.field").show</code>

Among them, field represents the name of the required field in the structure.

Access nested structure array

Fields in nested structure arrays can be accessed using a combination of dot syntax, field names, and the Column method:

Dot syntax

<code>df.select($"nestedArrayColumn.foo").show</code>

DataFrame API

<code>df.select($"nestedArrayColumn.vals".getItem(index).getItem(innerIndex)).show</code>

Additional Notes

• Fields in user-defined types (UDT) can be accessed using UDFs.
• For some operations involving nested data, it may be necessary to flatten the pattern or expand the collection.
• JSON columns can be queried using the get_json_object and from_json functions.

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