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https://issues.apache.org/jira/browse/BAHIR-39?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15406625#comment-15406625
]
ASF GitHub Bot commented on BAHIR-39:
-------------------------------------
Github user frreiss commented on a diff in the pull request:
https://github.com/apache/bahir/pull/13#discussion_r73422375
--- Diff:
sql-streaming-mqtt/src/main/scala/org/apache/bahir/sql/streaming/mqtt/MQTTStreamSource.scala
---
@@ -0,0 +1,191 @@
+/*
+ * 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.bahir.sql.streaming.mqtt
+
+import java.sql.Timestamp
+import java.text.SimpleDateFormat
+import java.util.Calendar
+import java.util.concurrent.CountDownLatch
+
+import scala.collection.concurrent.TrieMap
+import scala.collection.mutable.ArrayBuffer
+import scala.util.{Failure, Success, Try}
+
+import org.apache.bahir.utils.Logging
+import org.eclipse.paho.client.mqttv3._
+import org.eclipse.paho.client.mqttv3.persist.{MemoryPersistence,
MqttDefaultFilePersistence}
+
+import org.apache.spark.sql.{DataFrame, SQLContext}
+import org.apache.spark.sql.execution.streaming.{LongOffset, Offset,
Source}
+import org.apache.spark.sql.sources.{DataSourceRegister,
StreamSourceProvider}
+import org.apache.spark.sql.types.{StringType, StructField, StructType,
TimestampType}
+
+
+object MQTTStreamConstants {
+
+ val DATE_FORMAT = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss")
+
+ val SCHEMA_DEFAULT = StructType(StructField("value", StringType)
+ :: StructField("timestamp", TimestampType) :: Nil)
+}
+
+class MQTTTextStreamSource(brokerUrl: String, persistence:
MqttClientPersistence,
+ topic: String, clientId: String, messageParser: Array[Byte] =>
(String, Timestamp),
+ sqlContext: SQLContext) extends Source with Logging {
+
+ override def schema: StructType = MQTTStreamConstants.SCHEMA_DEFAULT
+
+ private val store = new LocalMessageStore(persistence,
sqlContext.sparkContext.getConf)
+
+ private val messages = new TrieMap[Int, (String, Timestamp)]
+
+ private val initLock = new CountDownLatch(1)
+
+ private var offset = 0
+
+ private var client: MqttClient = _
+
+ private def fetchLastProcessedOffset(): Int = {
+ Try(store.maxProcessedOffset) match {
+ case Success(x) =>
+ log.info(s"Recovering from last stored offset $x")
+ x
+ case Failure(e) => 0
+ }
+ }
+
+ initialize()
+ private def initialize(): Unit = {
+
+ client = new MqttClient(brokerUrl, clientId, persistence)
+ val mqttConnectOptions: MqttConnectOptions = new MqttConnectOptions()
+ mqttConnectOptions.setAutomaticReconnect(true)
+ // This is required to support recovery. TODO: configurable ?
+ mqttConnectOptions.setCleanSession(false)
+
+ val callback = new MqttCallbackExtended() {
+
+ override def messageArrived(topic_ : String, message: MqttMessage):
Unit = synchronized {
+ initLock.await() // Wait for initialization to complete.
+ val temp = offset + 1
+ messages.put(temp, messageParser(message.getPayload))
+ offset = temp
+ log.trace(s"Message arrived, $topic_ $message")
+ }
+
+ override def deliveryComplete(token: IMqttDeliveryToken): Unit = {
--- End diff --
I feel like this callback probably needs to do something to ensure that
there are no duplicate or out of order messages in the message buffer. What is
the interaction between these two callbacks (messageArrived/deliveryComplete)
and the different QoS levels in MQTT?
> MQTT as a streaming source for SQL Streaming.
> ---------------------------------------------
>
> Key: BAHIR-39
> URL: https://issues.apache.org/jira/browse/BAHIR-39
> Project: Bahir
> Issue Type: New Feature
> Components: Spark SQL Data Sources
> Affects Versions: 2.1.0
> Reporter: Prashant Sharma
>
> MQTT compatible streaming source for Spark SQL Streaming.
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