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Declarative Machine Learning
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysml.api.mlcontext;
import java.util.ArrayList;
import java.util.Date;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.log4j.Logger;
import org.apache.spark.SparkContext;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.SparkSession;
import org.apache.sysml.api.DMLScript;
import org.apache.sysml.api.DMLScript.RUNTIME_PLATFORM;
import org.apache.sysml.api.MLContextProxy;
import org.apache.sysml.api.jmlc.JMLCUtils;
import org.apache.sysml.conf.ConfigurationManager;
import org.apache.sysml.conf.DMLConfig;
import org.apache.sysml.parser.DataExpression;
import org.apache.sysml.parser.Expression;
import org.apache.sysml.parser.IntIdentifier;
import org.apache.sysml.parser.StringIdentifier;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.controlprogram.LocalVariableMap;
import org.apache.sysml.runtime.controlprogram.caching.MatrixObject;
import org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext;
import org.apache.sysml.runtime.instructions.Instruction;
import org.apache.sysml.runtime.instructions.cp.Data;
import org.apache.sysml.runtime.instructions.cp.ScalarObject;
import org.apache.sysml.runtime.matrix.MatrixFormatMetaData;
import org.apache.sysml.runtime.matrix.data.OutputInfo;
import org.apache.sysml.utils.Explain.ExplainType;
/**
* The MLContext API offers programmatic access to SystemML on Spark from
* languages such as Scala, Java, and Python.
*
*/
public class MLContext {
/**
* Logger for MLContext
*/
public static Logger log = Logger.getLogger(MLContext.class);
/**
* SparkSession object.
*/
private SparkSession spark = null;
/**
* Reference to the currently executing script.
*/
private Script executingScript = null;
/**
* The currently active MLContext.
*/
private static MLContext activeMLContext = null;
/**
* Contains cleanup methods used by MLContextProxy.
*/
private InternalProxy internalProxy = new InternalProxy();
/**
* Whether or not an explanation of the DML/PYDML program should be output
* to standard output.
*/
private boolean explain = false;
/**
* Whether or not statistics of the DML/PYDML program execution should be
* output to standard output.
*/
private boolean statistics = false;
/**
* Whether or not GPU mode should be enabled
*/
private boolean gpu = false;
/**
* The number of heavy hitters that are printed as part of the statistics
* option
*/
private int statisticsMaxHeavyHitters = 10;
/**
* The level and type of program explanation that should be displayed if
* explain is set to true.
*/
private ExplainLevel explainLevel = null;
/**
* Whether or not all values should be maintained in the symbol table
* after execution.
*/
private boolean maintainSymbolTable = false;
private List scriptHistoryStrings = new ArrayList();
private Map scripts = new LinkedHashMap();
/**
* The different explain levels supported by SystemML.
*
*/
public enum ExplainLevel {
/** Explain disabled */
NONE,
/** Explain program and HOPs */
HOPS,
/** Explain runtime program */
RUNTIME,
/** Explain HOPs, including recompile */
RECOMPILE_HOPS,
/** Explain runtime program, including recompile */
RECOMPILE_RUNTIME;
public ExplainType getExplainType() {
switch (this) {
case NONE:
return ExplainType.NONE;
case HOPS:
return ExplainType.HOPS;
case RUNTIME:
return ExplainType.RUNTIME;
case RECOMPILE_HOPS:
return ExplainType.RECOMPILE_HOPS;
case RECOMPILE_RUNTIME:
return ExplainType.RECOMPILE_RUNTIME;
default:
return ExplainType.HOPS;
}
}
};
/**
* Retrieve the currently active MLContext. This is used internally by
* SystemML via MLContextProxy.
*
* @return the active MLContext
*/
public static MLContext getActiveMLContext() {
return activeMLContext;
}
/**
* Create an MLContext based on a SparkSession for interaction with SystemML
* on Spark.
*
* @param spark SparkSession
*/
public MLContext(SparkSession spark) {
initMLContext(spark);
}
/**
* Create an MLContext based on a SparkContext for interaction with SystemML
* on Spark.
*
* @param sparkContext
* SparkContext
*/
public MLContext(SparkContext sparkContext) {
initMLContext(SparkSession.builder().sparkContext(sparkContext).getOrCreate());
}
/**
* Create an MLContext based on a JavaSparkContext for interaction with
* SystemML on Spark.
*
* @param javaSparkContext
* JavaSparkContext
*/
public MLContext(JavaSparkContext javaSparkContext) {
initMLContext(SparkSession.builder().sparkContext(javaSparkContext.sc()).getOrCreate());
}
/**
* Initialize MLContext. Verify Spark version supported, set default
* execution mode, set MLContextProxy, set default config, set compiler
* config.
*
* @param sc
* SparkContext object.
*/
private void initMLContext(SparkSession spark) {
try {
MLContextUtil.verifySparkVersionSupported(spark);
} catch (MLContextException e) {
if (info() != null) {
log.warn("Apache Spark " + this.info().minimumRecommendedSparkVersion() + " or above is recommended for SystemML " + this.info().version());
} else {
try {
String minSparkVersion = MLContextUtil.getMinimumRecommendedSparkVersionFromPom();
log.warn("Apache Spark " + minSparkVersion + " or above is recommended for this version of SystemML.");
} catch (MLContextException e1) {
log.error("Minimum recommended Spark version could not be determined from SystemML jar file manifest or pom.xml");
}
}
}
if (activeMLContext == null) {
System.out.println(MLContextUtil.welcomeMessage());
}
this.spark = spark;
// by default, run in hybrid Spark mode for optimal performance
DMLScript.rtplatform = RUNTIME_PLATFORM.HYBRID_SPARK;
activeMLContext = this;
MLContextProxy.setActive(true);
MLContextUtil.setDefaultConfig();
MLContextUtil.setCompilerConfig();
}
/**
* Reset configuration settings to default settings.
*/
public void resetConfig() {
MLContextUtil.setDefaultConfig();
}
/**
* Set configuration property, such as
* {@code setConfigProperty("localtmpdir", "/tmp/systemml")}.
*
* @param propertyName
* property name
* @param propertyValue
* property value
*/
public void setConfigProperty(String propertyName, String propertyValue) {
DMLConfig config = ConfigurationManager.getDMLConfig();
try {
config.setTextValue(propertyName, propertyValue);
} catch (DMLRuntimeException e) {
throw new MLContextException(e);
}
}
/**
* Execute a DML or PYDML Script.
*
* @param script
* The DML or PYDML Script object to execute.
* @return the results as a MLResults object
*/
public MLResults execute(Script script) {
ScriptExecutor scriptExecutor = new ScriptExecutor();
scriptExecutor.setExplain(explain);
scriptExecutor.setExplainLevel(explainLevel);
scriptExecutor.setGPU(gpu);
scriptExecutor.setStatistics(statistics);
scriptExecutor.setStatisticsMaxHeavyHitters(statisticsMaxHeavyHitters);
scriptExecutor.setInit(scriptHistoryStrings.isEmpty());
scriptExecutor.setMaintainSymbolTable(maintainSymbolTable);
return execute(script, scriptExecutor);
}
/**
* Execute a DML or PYDML Script object using a ScriptExecutor. The
* ScriptExecutor class can be extended to allow the modification of the
* default execution pathway.
*
* @param script
* the DML or PYDML Script object
* @param scriptExecutor
* the ScriptExecutor that defines the script execution pathway
* @return the results as a MLResults object
*/
public MLResults execute(Script script, ScriptExecutor scriptExecutor) {
try {
executingScript = script;
Long time = new Long((new Date()).getTime());
if ((script.getName() == null) || (script.getName().equals(""))) {
script.setName(time.toString());
}
MLResults results = scriptExecutor.execute(script);
String history = MLContextUtil.createHistoryForScript(script, time);
scriptHistoryStrings.add(history);
scripts.put(script.getName(), script);
return results;
} catch (RuntimeException e) {
throw new MLContextException("Exception when executing script", e);
}
}
/**
* Set SystemML configuration based on a configuration file.
*
* @param configFilePath
* path to the configuration file
*/
public void setConfig(String configFilePath) {
MLContextUtil.setConfig(configFilePath);
}
/**
* Obtain the SparkSession associated with this MLContext.
*
* @return the SparkSession associated with this MLContext.
*/
public SparkSession getSparkSession() {
return spark;
}
/**
* Whether or not an explanation of the DML/PYDML program should be output
* to standard output.
*
* @return {@code true} if explanation should be output, {@code false}
* otherwise
*/
public boolean isExplain() {
return explain;
}
/**
* Whether or not an explanation of the DML/PYDML program should be output
* to standard output.
*
* @param explain
* {@code true} if explanation should be output, {@code false}
* otherwise
*/
public void setExplain(boolean explain) {
this.explain = explain;
}
/**
* Obtain whether or not all values should be maintained in the symbol table
* after execution.
*
* @return {@code true} if all values should be maintained in the symbol
* table, {@code false} otherwise
*/
public boolean isMaintainSymbolTable() {
return maintainSymbolTable;
}
/**
* Set whether or not all values should be maintained in the symbol table
* after execution.
*
* @param maintainSymbolTable
* {@code true} if all values should be maintained in the symbol
* table, {@code false} otherwise
*/
public void setMaintainSymbolTable(boolean maintainSymbolTable) {
this.maintainSymbolTable = maintainSymbolTable;
}
/**
* Set the level of program explanation that should be displayed if explain
* is set to true.
*
* @param explainLevel
* the level of program explanation
*/
public void setExplainLevel(ExplainLevel explainLevel) {
this.explainLevel = explainLevel;
}
/**
* Set the level of program explanation that should be displayed if explain
* is set to true.
*
* @param explainLevel
* string denoting program explanation
*/
public void setExplainLevel(String explainLevel) {
if (explainLevel != null) {
for (ExplainLevel exp : ExplainLevel.values()) {
String expString = exp.toString();
if (expString.equalsIgnoreCase(explainLevel)) {
setExplainLevel(exp);
return;
}
}
}
throw new MLContextException("Failed to parse explain level: " + explainLevel + " "
+ "(valid types: hops, runtime, recompile_hops, recompile_runtime).");
}
/**
* Whether or not to use (an available) GPU on the driver node.
* If a GPU is not available, and the GPU mode is set, SystemML will crash when the program is run.
* @param enable
* true if needs to be enabled, false otherwise
*/
public void setGPU(boolean enable) {
this.gpu = enable;
}
/**
* Whether or not the GPU mode is enabled.
* @return true if enabled, false otherwise
*/
public boolean isGPU() {
return this.gpu;
}
/**
* Used internally by MLContextProxy.
*
*/
public class InternalProxy {
public void setAppropriateVarsForRead(Expression source, String target) {
boolean isTargetRegistered = isRegisteredAsInput(target);
boolean isReadExpression = (source instanceof DataExpression && ((DataExpression) source).isRead());
if (isTargetRegistered && isReadExpression) {
DataExpression exp = (DataExpression) source;
// Do not check metadata file for registered reads
exp.setCheckMetadata(false);
// Value retured from getVarParam is of type stringidentifier at
// runtime, but at compile type its Expression
// Could not find better way to compare this condition.
Expression datatypeExp = ((DataExpression) source).getVarParam("data_type");
String datatype = "matrix";
if (datatypeExp != null)
datatype = datatypeExp.toString();
if (datatype.compareToIgnoreCase("frame") != 0) {
MatrixObject mo = getMatrixObject(target);
if (mo != null) {
int blp = source.getBeginLine();
int bcp = source.getBeginColumn();
int elp = source.getEndLine();
int ecp = source.getEndColumn();
exp.addVarParam(DataExpression.READROWPARAM,
new IntIdentifier(mo.getNumRows(), source.getFilename(), blp, bcp, elp, ecp));
exp.addVarParam(DataExpression.READCOLPARAM,
new IntIdentifier(mo.getNumColumns(), source.getFilename(), blp, bcp, elp, ecp));
exp.addVarParam(DataExpression.READNUMNONZEROPARAM,
new IntIdentifier(mo.getNnz(), source.getFilename(), blp, bcp, elp, ecp));
exp.addVarParam(DataExpression.DATATYPEPARAM,
new StringIdentifier("matrix", source.getFilename(), blp, bcp, elp, ecp));
exp.addVarParam(DataExpression.VALUETYPEPARAM,
new StringIdentifier("double", source.getFilename(), blp, bcp, elp, ecp));
if (mo.getMetaData() instanceof MatrixFormatMetaData) {
MatrixFormatMetaData metaData = (MatrixFormatMetaData) mo.getMetaData();
if (metaData.getOutputInfo() == OutputInfo.CSVOutputInfo) {
exp.addVarParam(DataExpression.FORMAT_TYPE,
new StringIdentifier(DataExpression.FORMAT_TYPE_VALUE_CSV, source.getFilename(),
blp, bcp, elp, ecp));
} else if (metaData.getOutputInfo() == OutputInfo.TextCellOutputInfo) {
exp.addVarParam(DataExpression.FORMAT_TYPE,
new StringIdentifier(DataExpression.FORMAT_TYPE_VALUE_TEXT,
source.getFilename(), blp, bcp, elp, ecp));
} else if (metaData.getOutputInfo() == OutputInfo.BinaryBlockOutputInfo) {
exp.addVarParam(DataExpression.ROWBLOCKCOUNTPARAM, new IntIdentifier(
mo.getNumRowsPerBlock(), source.getFilename(), blp, bcp, elp, ecp));
exp.addVarParam(DataExpression.COLUMNBLOCKCOUNTPARAM, new IntIdentifier(
mo.getNumColumnsPerBlock(), source.getFilename(), blp, bcp, elp, ecp));
exp.addVarParam(DataExpression.FORMAT_TYPE,
new StringIdentifier(DataExpression.FORMAT_TYPE_VALUE_BINARY,
source.getFilename(), blp, bcp, elp, ecp));
} else {
throw new MLContextException("Unsupported format through MLContext");
}
}
}
}
}
}
private boolean isRegisteredAsInput(String parameterName) {
if (executingScript != null) {
Set inputVariableNames = executingScript.getInputVariables();
if (inputVariableNames != null) {
return inputVariableNames.contains(parameterName);
}
}
return false;
}
private MatrixObject getMatrixObject(String parameterName) {
if (executingScript != null) {
LocalVariableMap symbolTable = executingScript.getSymbolTable();
if (symbolTable != null) {
Data data = symbolTable.get(parameterName);
if (data instanceof MatrixObject) {
return (MatrixObject) data;
} else {
if (data instanceof ScalarObject) {
return null;
}
}
}
}
throw new MLContextException("getMatrixObject not set for parameter: " + parameterName);
}
public ArrayList performCleanupAfterRecompilation(ArrayList instructions) {
if (executingScript == null || executingScript.getOutputVariables() == null)
return instructions;
Set outputVariableNames = executingScript.getOutputVariables();
return JMLCUtils.cleanupRuntimeInstructions(instructions, outputVariableNames.toArray(new String[0]));
}
}
/**
* Used internally by MLContextProxy.
*
* @return InternalProxy object used by MLContextProxy
*/
public InternalProxy getInternalProxy() {
return internalProxy;
}
/**
* Whether or not statistics of the DML/PYDML program execution should be
* output to standard output.
*
* @return {@code true} if statistics should be output, {@code false}
* otherwise
*/
public boolean isStatistics() {
return statistics;
}
/**
* Whether or not statistics of the DML/PYDML program execution should be
* output to standard output.
*
* @param statistics
* {@code true} if statistics should be output, {@code false}
* otherwise
*/
public void setStatistics(boolean statistics) {
DMLScript.STATISTICS = statistics;
this.statistics = statistics;
}
/**
* Sets the maximum number of heavy hitters that are printed out as part of
* the statistics.
*
* @param maxHeavyHitters
* maximum number of heavy hitters to print
*/
public void setStatisticsMaxHeavyHitters(int maxHeavyHitters) {
DMLScript.STATISTICS_COUNT = maxHeavyHitters;
this.statisticsMaxHeavyHitters = maxHeavyHitters;
}
/**
* Obtain a map of the scripts that have executed.
*
* @return a map of the scripts that have executed
*/
public Map getScripts() {
return scripts;
}
/**
* Obtain a script that has executed by name.
*
* @param name
* the name of the script
* @return the script corresponding to the name
*/
public Script getScriptByName(String name) {
Script script = scripts.get(name);
if (script == null) {
throw new MLContextException("Script with name '" + name + "' not found.");
}
return script;
}
/**
* Display the history of scripts that have executed.
*
* @return the history of scripts that have executed
*/
public String history() {
return MLContextUtil.displayScriptHistory(scriptHistoryStrings);
}
/**
* Closes the mlcontext, which includes the cleanup of static and local
* state as well as scratch space and buffer pool cleanup. Note that the
* spark context is not explicitly closed to allow external reuse.
*/
public void close() {
// reset static status (refs to sc / mlcontext)
SparkExecutionContext.resetSparkContextStatic();
MLContextProxy.setActive(false);
activeMLContext = null;
// cleanup scratch space and buffer pool
try {
DMLScript.cleanupHadoopExecution(ConfigurationManager.getDMLConfig());
} catch (Exception ex) {
throw new MLContextException("Failed to cleanup working directories.", ex);
}
// clear local status, but do not stop sc as it
// may be used or stopped externally
for (Script script : scripts.values())
script.clearAll();
scripts.clear();
scriptHistoryStrings.clear();
resetConfig();
spark = null;
}
/**
* Obtain information about the project such as version and build time from
* the manifest in the SystemML jar file.
*
* @return information about the project
*/
public ProjectInfo info() {
try {
ProjectInfo projectInfo = ProjectInfo.getProjectInfo();
return projectInfo;
} catch (Exception e) {
log.warn("Project information not available");
return null;
}
}
/**
* Obtain the SystemML version number.
*
* @return the SystemML version number
*/
public String version() {
if (info() == null) {
return "Version not available";
}
return info().version();
}
/**
* Obtain the SystemML jar file build time.
*
* @return the SystemML jar file build time
*/
public String buildTime() {
if (info() == null) {
return "Build time not available";
}
return info().buildTime();
}
}