org.apache.spark.sql.streaming

Class DataStreamReader

Object

org.apache.spark.sql.streaming.DataStreamReader

All Implemented Interfaces:

org.apache.spark.internal.Logging

public final class DataStreamReader
extends Object
implements org.apache.spark.internal.Logging

Interface used to load a streaming Dataset from external storage systems (e.g. file systems, key-value stores, etc). Use SparkSession.readStream to access this.

Since:

2.0.0

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method and Description
Dataset<Row>	csv(String path) Loads a CSV file stream and returns the result as a DataFrame.
DataStreamReader	format(String source) Specifies the input data source format.
Dataset<Row>	json(String path) Loads a JSON file stream and returns the results as a DataFrame.
Dataset<Row>	load() Loads input data stream in as a DataFrame, for data streams that don't require a path (e.g.
Dataset<Row>	load(String path) Loads input in as a DataFrame, for data streams that read from some path.
DataStreamReader	option(String key, boolean value) Adds an input option for the underlying data source.
DataStreamReader	option(String key, double value) Adds an input option for the underlying data source.
DataStreamReader	option(String key, long value) Adds an input option for the underlying data source.
DataStreamReader	option(String key, String value) Adds an input option for the underlying data source.
DataStreamReader	options(scala.collection.Map<String,String> options) (Scala-specific) Adds input options for the underlying data source.
DataStreamReader	options(java.util.Map<String,String> options) (Java-specific) Adds input options for the underlying data source.
Dataset<Row>	orc(String path) Loads a ORC file stream, returning the result as a DataFrame.
Dataset<Row>	parquet(String path) Loads a Parquet file stream, returning the result as a DataFrame.
DataStreamReader	schema(String schemaString) Specifies the schema by using the input DDL-formatted string.
DataStreamReader	schema(StructType schema) Specifies the input schema.
Dataset<Row>	table(String tableName) Define a Streaming DataFrame on a Table.
Dataset<Row>	text(String path) Loads text files and returns a DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any.
Dataset<String>	textFile(String path) Loads text file(s) and returns a Dataset of String.

Methods inherited from class Object

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

Methods inherited from interface org.apache.spark.internal.Logging

$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Method Detail

csv

public Dataset<Row> csv(String path)

Loads a CSV file stream and returns the result as a DataFrame.

This function will go through the input once to determine the input schema if inferSchema is enabled. To avoid going through the entire data once, disable inferSchema option or specify the schema explicitly using schema.

You can set the following option(s):

• maxFilesPerTrigger (default: no max limit): sets the maximum number of new files to be considered in every trigger.

You can find the CSV-specific options for reading CSV file stream in Data Source Option in the version you use.

Parameters:

path - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

format

public DataStreamReader format(String source)

Specifies the input data source format.

Parameters:

source - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

json

public Dataset<Row> json(String path)

Loads a JSON file stream and returns the results as a DataFrame.

JSON Lines (newline-delimited JSON) is supported by default. For JSON (one record per file), set the multiLine option to true.

This function goes through the input once to determine the input schema. If you know the schema in advance, use the version that specifies the schema to avoid the extra scan.

You can set the following option(s):

• maxFilesPerTrigger (default: no max limit): sets the maximum number of new files to be considered in every trigger.

You can find the JSON-specific options for reading JSON file stream in Data Source Option in the version you use.

Parameters:

path - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

load

public Dataset<Row> load()

Loads input data stream in as a DataFrame, for data streams that don't require a path (e.g. external key-value stores).

Returns:

(undocumented)

Since:

2.0.0

load

public Dataset<Row> load(String path)

Loads input in as a DataFrame, for data streams that read from some path.

Parameters:

path - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

option

public DataStreamReader option(String key,
                               String value)

Adds an input option for the underlying data source.

Parameters:

key - (undocumented)

value - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

option

public DataStreamReader option(String key,
                               boolean value)

Adds an input option for the underlying data source.

Parameters:

key - (undocumented)

value - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

option

public DataStreamReader option(String key,
                               long value)

Adds an input option for the underlying data source.

Parameters:

key - (undocumented)

value - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

option

public DataStreamReader option(String key,
                               double value)

Adds an input option for the underlying data source.

Parameters:

key - (undocumented)

value - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

options

public DataStreamReader options(scala.collection.Map<String,String> options)

(Scala-specific) Adds input options for the underlying data source.

Parameters:

options - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

options

public DataStreamReader options(java.util.Map<String,String> options)

(Java-specific) Adds input options for the underlying data source.

Parameters:

options - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

orc

public Dataset<Row> orc(String path)

Loads a ORC file stream, returning the result as a DataFrame.

You can set the following option(s):

• maxFilesPerTrigger (default: no max limit): sets the maximum number of new files to be considered in every trigger.

ORC-specific option(s) for reading ORC file stream can be found in Data Source Option in the version you use.

Parameters:

path - (undocumented)

Returns:

(undocumented)

Since:

2.3.0

parquet

public Dataset<Row> parquet(String path)

Loads a Parquet file stream, returning the result as a DataFrame.

You can set the following option(s):

• maxFilesPerTrigger (default: no max limit): sets the maximum number of new files to be considered in every trigger.

Parquet-specific option(s) for reading Parquet file stream can be found in Data Source Option in the version you use.

Parameters:

path - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

schema

public DataStreamReader schema(StructType schema)

Specifies the input schema. Some data sources (e.g. JSON) can infer the input schema automatically from data. By specifying the schema here, the underlying data source can skip the schema inference step, and thus speed up data loading.

Parameters:

schema - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

schema

public DataStreamReader schema(String schemaString)

Specifies the schema by using the input DDL-formatted string. Some data sources (e.g. JSON) can infer the input schema automatically from data. By specifying the schema here, the underlying data source can skip the schema inference step, and thus speed up data loading.

Parameters:

schemaString - (undocumented)

Returns:

(undocumented)

Since:

2.3.0

table

public Dataset<Row> table(String tableName)

Define a Streaming DataFrame on a Table. The DataSource corresponding to the table should support streaming mode.

Parameters:

tableName - The name of the table

Returns:

(undocumented)

Since:

3.1.0

text

public Dataset<Row> text(String path)

Loads text files and returns a DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any. The text files must be encoded as UTF-8.

By default, each line in the text files is a new row in the resulting DataFrame. For example:

   // Scala:
   spark.readStream.text("/path/to/directory/")

   // Java:
   spark.readStream().text("/path/to/directory/")
 

You can set the following option(s):

• maxFilesPerTrigger (default: no max limit): sets the maximum number of new files to be considered in every trigger.

You can find the text-specific options for reading text files in Data Source Option in the version you use.

Parameters:

path - (undocumented)

Returns:

(undocumented)

Since:

2.0.0

textFile

public Dataset<String> textFile(String path)

Loads text file(s) and returns a Dataset of String. The underlying schema of the Dataset contains a single string column named "value". The text files must be encoded as UTF-8.

If the directory structure of the text files contains partitioning information, those are ignored in the resulting Dataset. To include partitioning information as columns, use text.

By default, each line in the text file is a new element in the resulting Dataset. For example:

   // Scala:
   spark.readStream.textFile("/path/to/spark/README.md")

   // Java:
   spark.readStream().textFile("/path/to/spark/README.md")
 

You can set the text-specific options as specified in DataStreamReader.text.

Parameters:

path - input path

Returns:

(undocumented)

Since:

2.1.0