本文整理了Java中org.apache.spark.sql.DataFrame.schema()方法的一些代码示例，展示了DataFrame.schema()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。DataFrame.schema()方法的具体详情如下：
包路径：org.apache.spark.sql.DataFrame
类名称：DataFrame
方法名：schema

DataFrame.schema介绍

暂无

代码示例

代码示例来源：origin: stackoverflow.com

DataFrame df;
SQLContext sqlContext;
Long start;
Long end;

JavaPairRDD<Row, Long> indexedRDD = df.toJavaRDD().zipWithIndex();
JavaRDD filteredRDD = indexedRDD.filter((Tuple2<Row,Long> v1) -> v1._2 >= start && v1._2 < end);
DataFrame filteredDataFrame = sqlContext.createDataFrame(filteredRDD, df.schema());

代码示例来源：origin: org.wso2.carbon.analytics/org.wso2.carbon.analytics.spark.core

public static List<Record> dataFrameToRecordsList(int tenantId, String tableName,
                         DataFrame dataFrame) {
  Row[] rows = dataFrame.collect();
  List<Record> records = new ArrayList<>();
  StructType schema = dataFrame.schema();
  for (Row row : rows) {
    records.add(new Record(tenantId, tableName, convertRowAndSchemaToValuesMap(row, schema)));
  }
  return records;
}

代码示例来源：origin: org.wso2.carbon.analytics/org.wso2.carbon.analytics.spark.core

private AnalyticsQueryResult toResult(DataFrame dataFrame)
    throws AnalyticsExecutionException {
  int resultsLimit = this.sparkConf.getInt("carbon.spark.results.limit", -1);
  if (resultsLimit != -1) {
    return new AnalyticsQueryResult(dataFrame.schema().fieldNames(),
        convertRowsToObjects(dataFrame.limit(resultsLimit).collect()));
  } else {
    return new AnalyticsQueryResult(dataFrame.schema().fieldNames(),
        convertRowsToObjects(dataFrame.collect()));
  }
}

代码示例来源：origin: flipkart-incubator/spark-transformers

@Override
public OneHotEncoderModelInfo getModelInfo(final OneHotEncoder from, DataFrame df) {
  OneHotEncoderModelInfo modelInfo = new OneHotEncoderModelInfo();
  String inputColumn = from.getInputCol();
  //Ugly but the only way to deal with spark here
  int numTypes = -1;
  Attribute attribute = Attribute.fromStructField(df.schema().apply(inputColumn));
  if (attribute.attrType() == AttributeType.Nominal()) {
    numTypes = ((NominalAttribute) Attribute.fromStructField(df.schema().apply(inputColumn))).values().get().length;
  } else if (attribute.attrType() == AttributeType.Binary()) {
    numTypes = ((BinaryAttribute) Attribute.fromStructField(df.schema().apply(inputColumn))).values().get().length;
  }
  //TODO: Since dropLast is not accesible here, We are deliberately setting numTypes. This is the reason, we should use CustomOneHotEncoder
  modelInfo.setNumTypes(numTypes - 1);
  Set<String> inputKeys = new LinkedHashSet<String>();
  inputKeys.add(from.getInputCol());
  modelInfo.setInputKeys(inputKeys);
  Set<String> outputKeys = new LinkedHashSet<String>();
  outputKeys.add(from.getOutputCol());
  modelInfo.setOutputKeys(outputKeys);
  return modelInfo;
}

代码示例来源：origin: org.wso2.carbon.analytics/org.wso2.carbon.analytics.spark.core

private void writeDataFrameToDAL(DataFrame data) {
  if (this.preserveOrder) {
    logDebug("Inserting data with order preserved! Each partition will be written using separate jobs.");
    for (int i = 0; i < data.rdd().partitions().length; i++) {
      data.sqlContext().sparkContext().runJob(data.rdd(),
                          new AnalyticsWritingFunction(this.tenantId, this.tableName, data.schema(),
                                         this.globalTenantAccess, this.schemaString, this.primaryKeys, this.mergeFlag,
                                         this.recordStore, this.recordBatchSize), CarbonScalaUtils.getNumberSeq(i, i + 1),
                          false, ClassTag$.MODULE$.Unit());
    }
  } else {
    data.foreachPartition(new AnalyticsWritingFunction(this.tenantId, this.tableName, data.schema(),
                              this.globalTenantAccess, this.schemaString, this.primaryKeys, this.mergeFlag,
                              this.recordStore, this.recordBatchSize));
  }
}