org.apache.iceberg.spark

Class SparkSchemaUtil

java.lang.Object

org.apache.iceberg.spark.SparkSchemaUtil

public class SparkSchemaUtil
extends java.lang.Object

Helper methods for working with Spark/Hive metadata.

Method Summary

Modifier and Type	Method and Description
static Type	convert(org.apache.spark.sql.types.DataType sparkType) Convert a Spark struct to a Type with new field ids.
static org.apache.spark.sql.types.StructType	convert(Schema schema) Convert a Schema to a Spark type.
static Schema	convert(Schema baseSchema, org.apache.spark.sql.types.StructType sparkType) Convert a Spark struct to a Schema based on the given schema.
static Schema	convert(org.apache.spark.sql.types.StructType sparkType) Convert a Spark struct to a Schema with new field ids.
static org.apache.spark.sql.types.DataType	convert(Type type) Convert a Type to a Spark type.
static long	estimateSize(org.apache.spark.sql.types.StructType tableSchema, long totalRecords) estimate approximate table size based on spark schema and total records.
static Schema	prune(Schema schema, org.apache.spark.sql.types.StructType requestedType) Prune columns from a Schema using a Spark type projection.
static Schema	prune(Schema schema, org.apache.spark.sql.types.StructType requestedType, Expression filter, boolean caseSensitive) Prune columns from a Schema using a Spark type projection.
static Schema	prune(Schema schema, org.apache.spark.sql.types.StructType requestedType, java.util.List<Expression> filters) Prune columns from a Schema using a Spark type projection.
static Schema	schemaForTable(org.apache.spark.sql.SparkSession spark, java.lang.String name) Returns a Schema for the given table with fresh field ids.
static PartitionSpec	specForTable(org.apache.spark.sql.SparkSession spark, java.lang.String name) Returns a PartitionSpec for the given table.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

schemaForTable

public static Schema schemaForTable(org.apache.spark.sql.SparkSession spark,
                                    java.lang.String name)

Returns a Schema for the given table with fresh field ids.

This creates a Schema for an existing table by looking up the table's schema with Spark and converting that schema. Spark/Hive partition columns are included in the schema.

Parameters:

spark - a Spark session

name - a table name and (optional) database

Returns:

a Schema for the table, if found

specForTable

public static PartitionSpec specForTable(org.apache.spark.sql.SparkSession spark,
                                         java.lang.String name)
                                  throws org.apache.spark.sql.AnalysisException

Returns a PartitionSpec for the given table.

This creates a partition spec for an existing table by looking up the table's schema and creating a spec with identity partitions for each partition column.

Parameters:

spark - a Spark session

name - a table name and (optional) database

Returns:

a PartitionSpec for the table

Throws:

org.apache.spark.sql.AnalysisException - if thrown by the Spark catalog

convert

public static org.apache.spark.sql.types.StructType convert(Schema schema)

Convert a Schema to a Spark type.

Parameters:

schema - a Schema

Returns:

the equivalent Spark type

Throws:

java.lang.IllegalArgumentException - if the type cannot be converted to Spark

convert

public static org.apache.spark.sql.types.DataType convert(Type type)

Convert a Type to a Spark type.

Parameters:

type - a Type

Returns:

the equivalent Spark type

Throws:

java.lang.IllegalArgumentException - if the type cannot be converted to Spark

convert

public static Schema convert(org.apache.spark.sql.types.StructType sparkType)

Convert a Spark struct to a Schema with new field ids.

This conversion assigns fresh ids.

Some data types are represented as the same Spark type. These are converted to a default type.

To convert using a reference schema for field ids and ambiguous types, use convert(Schema, StructType).

Parameters:

sparkType - a Spark StructType

Returns:

the equivalent Schema

Throws:

java.lang.IllegalArgumentException - if the type cannot be converted

convert

public static Type convert(org.apache.spark.sql.types.DataType sparkType)

Convert a Spark struct to a Type with new field ids.

This conversion assigns fresh ids.

Some data types are represented as the same Spark type. These are converted to a default type.

To convert using a reference schema for field ids and ambiguous types, use convert(Schema, StructType).

Parameters:

sparkType - a Spark DataType

Returns:

the equivalent Type

Throws:

java.lang.IllegalArgumentException - if the type cannot be converted

convert

public static Schema convert(Schema baseSchema,
                             org.apache.spark.sql.types.StructType sparkType)

Convert a Spark struct to a Schema based on the given schema.

This conversion does not assign new ids; it uses ids from the base schema.

Data types, field order, and nullability will match the spark type. This conversion may return a schema that is not compatible with base schema.

Parameters:

baseSchema - a Schema on which conversion is based

sparkType - a Spark StructType

Returns:

the equivalent Schema

Throws:

java.lang.IllegalArgumentException - if the type cannot be converted or there are missing ids

prune

public static Schema prune(Schema schema,
                           org.apache.spark.sql.types.StructType requestedType)

Prune columns from a Schema using a Spark type projection.

This requires that the Spark type is a projection of the Schema. Nullability and types must match.

Parameters:

schema - a Schema

requestedType - a projection of the Spark representation of the Schema

Returns:

a Schema corresponding to the Spark projection

Throws:

java.lang.IllegalArgumentException - if the Spark type does not match the Schema

prune

public static Schema prune(Schema schema,
                           org.apache.spark.sql.types.StructType requestedType,
                           java.util.List<Expression> filters)

Prune columns from a Schema using a Spark type projection.

This requires that the Spark type is a projection of the Schema. Nullability and types must match.

The filters list of Expression is used to ensure that columns referenced by filters are projected.

Parameters:

schema - a Schema

requestedType - a projection of the Spark representation of the Schema

filters - a list of filters

Returns:

a Schema corresponding to the Spark projection

Throws:

java.lang.IllegalArgumentException - if the Spark type does not match the Schema

prune

public static Schema prune(Schema schema,
                           org.apache.spark.sql.types.StructType requestedType,
                           Expression filter,
                           boolean caseSensitive)

Prune columns from a Schema using a Spark type projection.

This requires that the Spark type is a projection of the Schema. Nullability and types must match.

The filters list of Expression is used to ensure that columns referenced by filters are projected.

Parameters:

schema - a Schema

requestedType - a projection of the Spark representation of the Schema

filter - a filters

Returns:

a Schema corresponding to the Spark projection

Throws:

java.lang.IllegalArgumentException - if the Spark type does not match the Schema

estimateSize

public static long estimateSize(org.apache.spark.sql.types.StructType tableSchema,
                                long totalRecords)

estimate approximate table size based on spark schema and total records.

Parameters:

tableSchema - spark schema

totalRecords - total records in the table

Returns:

approxiate size based on table schema