Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14491
Could you look through these as below? at least I found one more.
```
src/main/java/org/apache/spark/examples/ml/JavaDecisionTreeClassificationExample.java:
// Load the data stored in LIBSVM format as a DataFrame.
src/main/java/org/apache/spark/examples/ml/JavaDecisionTreeRegressionExample.java:
// Load the data stored in LIBSVM format as a DataFrame.
src/main/java/org/apache/spark/examples/ml/JavaGradientBoostedTreeClassifierExample.java:
// Load and parse the data file, converting it to a DataFrame.
src/main/java/org/apache/spark/examples/ml/JavaGradientBoostedTreeRegressorExample.java:
// Load and parse the data file, converting it to a DataFrame.
src/main/java/org/apache/spark/examples/ml/JavaRandomForestClassifierExample.java:
// Load and parse the data file, converting it to a DataFrame.
src/main/java/org/apache/spark/examples/ml/JavaRandomForestRegressorExample.java:
// Load and parse the data file, converting it to a DataFrame.
src/main/java/org/apache/spark/examples/sql/hive/JavaSparkHiveExample.java:
// The results of SQL queries are themselves DataFrames and support all
normal functions.
src/main/java/org/apache/spark/examples/sql/hive/JavaSparkHiveExample.java:
// You can also use DataFrames to create temporary views within a
SparkSession.
src/main/java/org/apache/spark/examples/sql/hive/JavaSparkHiveExample.java:
// Queries can then join DataFrames data with data stored in Hive.
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
Displays the content of the DataFrame to stdout
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
Register the DataFrame as a SQL temporary view
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
DataFrames can be converted to a Dataset by providing a class. Mapping based on
name
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
Apply a schema to an RDD of JavaBeans to get a DataFrame
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
Register the DataFrame as a temporary view
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
Creates a temporary view using the DataFrame
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
SQL can be run over a temporary view created using DataFrames
src/main/java/org/apache/spark/examples/sql/JavaSparkSQLExample.java: //
The results of SQL queries are DataFrames and support all the normal RDD
operations
src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:
// DataFrames can be saved as Parquet files, maintaining the schema
information
src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:
// The result of loading a parquet file is also a DataFrame
src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:
// Create a simple DataFrame, store into a partition directory
src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:
// Create another DataFrame in a new partition directory,
src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:
// Creates a temporary view using the DataFrame
src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCount.java:
// Create DataFrame representing the stream of input lines from connection
to host:port
src/main/java/org/apache/spark/examples/sql/streaming/JavaStructuredNetworkWordCountWindowed.java:
// Create DataFrame representing the stream of input lines from connection
to host:port
src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java:
* Use DataFrames and SQL to count words in UTF8 encoded, '\n' delimited text
received from the
src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java:
// Convert RDDs of the words DStream to DataFrame and run SQL query
src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java:
// Convert JavaRDD[String] to JavaRDD[bean class] to DataFrame
src/main/java/org/apache/spark/examples/streaming/JavaSqlNetworkWordCount.java:
// Creates a temporary view using the DataFrame
src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala: * An
example of how to use [[org.apache.spark.sql.DataFrame]] for ML. Run with
src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala:
// Load the data stored in LIBSVM format as a DataFrame.
src/main/scala/org/apache/spark/examples/ml/DecisionTreeExample.scala: *
@param data DataFrame with "prediction" and labelColName columns
src/main/scala/org/apache/spark/examples/ml/DecisionTreeExample.scala: *
@param data DataFrame with "prediction" and labelColName columns
src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala:
// Load the data stored in LIBSVM format as a DataFrame.
src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala:
// Load and parse the data file, converting it to a DataFrame.
src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala:
// Load and parse the data file, converting it to a DataFrame.
src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala:
// Load the data stored in LIBSVM format as a DataFrame.
src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala: //
Load the data stored in LIBSVM format as a DataFrame.
src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala:
// Load and parse the data file, converting it to a DataFrame.
src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala:
// Load and parse the data file, converting it to a DataFrame.
src/main/scala/org/apache/spark/examples/sql/hive/SparkHiveExample.scala:
// The results of SQL queries are themselves DataFrames and support all normal
functions.
src/main/scala/org/apache/spark/examples/sql/hive/SparkHiveExample.scala:
// You can also use DataFrames to create temporary views within a SparkSession.
src/main/scala/org/apache/spark/examples/sql/hive/SparkHiveExample.scala:
// Queries can then join DataFrame data with data stored in Hive.
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
For implicit conversions like converting RDDs to DataFrames
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
Displays the content of the DataFrame to stdout
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
Register the DataFrame as a SQL temporary view
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
DataFrames can be converted to a Dataset by providing a class. Mapping will be
done by name
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
For implicit conversions from RDDs to DataFrames
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
Register the DataFrame as a temporary view
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
Creates a temporary view using the DataFrame
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
SQL can be run over a temporary view created using DataFrames
src/main/scala/org/apache/spark/examples/sql/SparkSQLExample.scala: //
The results of SQL queries are DataFrames and support all the normal RDD
operations
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// DataFrames can be saved as Parquet files, maintaining the schema information
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// The result of loading a Parquet file is also a DataFrame
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// This is used to implicitly convert an RDD to a DataFrame.
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// Create a simple DataFrame, store into a partition directory
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// Create another DataFrame in a new partition directory,
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// Creates a temporary view using the DataFrame
src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala:
// Alternatively, a DataFrame can be created for a JSON dataset represented by
src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCount.scala:
// Create DataFrame representing the stream of input lines from connection
to host:port
src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCountWindowed.scala:
// Create DataFrame representing the stream of input lines from connection
to host:port
src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala: *
Use DataFrames and SQL to count words in UTF8 encoded, '\n' delimited text
received from the
src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala:
// Convert RDDs of the words DStream to DataFrame and run SQL query
src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala:
// Convert RDD[String] to RDD[case class] to DataFrame
src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala:
// Creates a temporary view using the DataFrame
src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala:/**
Case class for converting RDD to DataFrame */
```
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
