org.elasticsearch.spark.sql.EsSparkSQL.scala Maven / Gradle / Ivy
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package org.elasticsearch.spark.sql
import org.apache.commons.logging.LogFactory
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.Dataset
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.SparkSession
import org.elasticsearch.hadoop.EsHadoopIllegalArgumentException
import org.elasticsearch.hadoop.cfg.ConfigurationOptions.ES_QUERY
import org.elasticsearch.hadoop.cfg.ConfigurationOptions.ES_RESOURCE_READ
import org.elasticsearch.hadoop.cfg.ConfigurationOptions.ES_RESOURCE_WRITE
import org.elasticsearch.hadoop.cfg.PropertiesSettings
import org.elasticsearch.hadoop.mr.security.HadoopUserProvider
import org.elasticsearch.hadoop.rest.InitializationUtils
import org.elasticsearch.hadoop.util.ObjectUtils
import org.elasticsearch.spark.cfg.SparkSettingsManager
import scala.collection.JavaConverters.mapAsJavaMapConverter
import scala.collection.JavaConverters.propertiesAsScalaMapConverter
import scala.collection.Map
object EsSparkSQL {
private val init = { ObjectUtils.loadClass("org.elasticsearch.spark.rdd.CompatUtils", classOf[ObjectUtils].getClassLoader) }
@transient private[this] val LOG = LogFactory.getLog(EsSparkSQL.getClass)
//
// Read
//
def esDF(sc: SQLContext): DataFrame = esDF(sc, Map.empty[String, String])
def esDF(sc: SQLContext, resource: String): DataFrame = esDF(sc, Map(ES_RESOURCE_READ -> resource))
def esDF(sc: SQLContext, resource: String, query: String): DataFrame = esDF(sc, Map(ES_RESOURCE_READ -> resource, ES_QUERY -> query))
def esDF(sc: SQLContext, cfg: Map[String, String]): DataFrame = {
val esConf = new SparkSettingsManager().load(sc.sparkContext.getConf).copy()
esConf.merge(cfg.asJava)
sc.read.format("org.elasticsearch.spark.sql").options(esConf.asProperties.asScala.toMap).load
}
def esDF(sc: SQLContext, resource: String, query: String, cfg: Map[String, String]): DataFrame = {
esDF(sc, collection.mutable.Map(cfg.toSeq: _*) += (ES_RESOURCE_READ -> resource, ES_QUERY -> query))
}
def esDF(sc: SQLContext, resource: String, cfg: Map[String, String]): DataFrame = {
esDF(sc, collection.mutable.Map(cfg.toSeq: _*) += (ES_RESOURCE_READ -> resource))
}
// SparkSession variant
def esDF(ss: SparkSession): DataFrame = esDF(ss.sqlContext, Map.empty[String, String])
def esDF(ss: SparkSession, resource: String): DataFrame = esDF(ss.sqlContext, Map(ES_RESOURCE_READ -> resource))
def esDF(ss: SparkSession, resource: String, query: String): DataFrame = esDF(ss.sqlContext, Map(ES_RESOURCE_READ -> resource, ES_QUERY -> query))
def esDF(ss: SparkSession, cfg: Map[String, String]): DataFrame = esDF(ss.sqlContext, cfg)
def esDF(ss: SparkSession, resource: String, query: String, cfg: Map[String, String]): DataFrame = esDF(ss.sqlContext, resource, query, cfg)
def esDF(ss: SparkSession, resource: String, cfg: Map[String, String]): DataFrame = esDF(ss.sqlContext, resource, cfg)
//
// Write
//
def saveToEs(srdd: Dataset[_], resource: String): Unit = {
saveToEs(srdd, Map(ES_RESOURCE_WRITE -> resource))
}
def saveToEs(srdd: Dataset[_], resource: String, cfg: Map[String, String]): Unit = {
saveToEs(srdd, collection.mutable.Map(cfg.toSeq: _*) += (ES_RESOURCE_WRITE -> resource))
}
def saveToEs(srdd: Dataset[_], cfg: Map[String, String]): Unit = {
if (srdd != null) {
if (srdd.isStreaming) {
throw new EsHadoopIllegalArgumentException("Streaming Datasets should not be saved with 'saveToEs()'. Instead, use " +
"the 'writeStream().format(\"es\").save()' methods.")
}
val sparkCtx = srdd.sqlContext.sparkContext
val sparkCfg = new SparkSettingsManager().load(sparkCtx.getConf)
val esCfg = new PropertiesSettings().load(sparkCfg.save())
esCfg.merge(cfg.asJava)
// Need to discover ES Version before checking index existence
InitializationUtils.setUserProviderIfNotSet(esCfg, classOf[HadoopUserProvider], LOG)
InitializationUtils.discoverClusterInfo(esCfg, LOG)
InitializationUtils.checkIdForOperation(esCfg)
InitializationUtils.checkIndexExistence(esCfg)
sparkCtx.runJob(srdd.toDF().rdd, new EsDataFrameWriter(srdd.schema, esCfg.save()).write _)
}
}
}
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