Hi Stephen/All,
got it working somewhat using below, but have an issue table and data which
is created using thin client is failing to read using spark but table
created by spark can be read using a thin client, that means table created
in Ignite using spark are the only ones read using spark in Ignite?
example-default.xml
<property name="addresses">
<list>
<!-- In distributed environment, replace with actual host IP
address. -->
<value>18.206.247.40:10800</value>
</list>
</property>
NotWorking Scala Function:-
def readThinClientTableUsingSpark(implicit spark: SparkSession) = {
val personDataFrame = spark.read
.format(FORMAT_IGNITE)
.option(OPTION_CONFIG_FILE, CONFIG)
.option(OPTION_TABLE, "person")
.load()
println()
println("Data frame thin connection content:person")
println()
//Printing content of data frame to console.
personDataFrame.show()
}
*Exception in thread "main" class org.apache.ignite.IgniteException:
Unknown table person at
org.apache.ignite.spark.impl.IgniteSQLRelation$$anonfun$schema$2.apply(IgniteSQLRelation.scala:46)
at
org.apache.ignite.spark.impl.IgniteSQLRelation$$anonfun$schema$2.apply(IgniteSQLRelation.scala:46)
at scala.Option.getOrElse(Option.scala:121) at
org.apache.ignite.spark.impl.IgniteSQLRelation.schema(IgniteSQLRelation.scala:46)
at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:431)
at
org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227) at
org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164) at
com.ignite.examples.spark.SparkIgniteCleanCode$.readThinClientTableUsingSpark(SparkIgniteCleanCode.scala:154)
at
com.ignite.examples.spark.SparkIgniteCleanCode$.main(SparkIgniteCleanCode.scala:216)
at
com.ignite.examples.spark.SparkIgniteCleanCode.main(SparkIgniteCleanCode.scala)*
*Full Code:- (step 7 Fails)*
package com.ignite.examples.spark
import com.ignite.examples.model.Address
import org.apache.ignite.{Ignite, Ignition}
import org.apache.ignite.cache.query.SqlFieldsQuery
import org.apache.ignite.client.{ClientCache, IgniteClient}
import org.apache.ignite.configuration.{CacheConfiguration, ClientConfiguration}
import java.lang.{Long => JLong, String => JString}
import com.ignite.examples.spark.SparkClientConnectionTest.{CACHE_NAME, CONFIG}
import org.apache.ignite.internal.util.IgniteUtils.resolveIgnitePath
import org.apache.ignite.spark.IgniteDataFrameSettings.{FORMAT_IGNITE,
OPTION_CONFIG_FILE, OPTION_CREATE_TABLE_PARAMETERS,
OPTION_CREATE_TABLE_PRIMARY_KEY_FIELDS, OPTION_TABLE}
import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.{SaveMode, SparkSession}
object SparkIgniteCleanCode {
private val CACHE_NAME = "SparkCache"
private val CONFIG =
"/Users/kalit_000/Downloads/designing-event-driven-applications-apache-kafka-ecosystem/05/demos/kafka-streams-after/ApacheIgnitePoc/src/main/scala/com/ignite/examples/config/example-ignite.xml"
def setupExampleData = {
val cfg2 = new ClientConfiguration().setAddresses("18.206.247.40:10800")
val igniteClient:IgniteClient = Ignition.startClient(cfg2)
System.out.format(">>> Created cache [%s].\n", CACHE_NAME)
val cache:ClientCache[Integer, Address] =
igniteClient.getOrCreateCache(CACHE_NAME)
cache.query(new SqlFieldsQuery(String.format("DROP TABLE IF EXISTS Person"))
.setSchema("PUBLIC")).getAll
cache.query(new SqlFieldsQuery(String.format("CREATE TABLE IF NOT
EXISTS Person (id LONG,street varchar, zip VARCHAR, PRIMARY KEY (id) )
WITH \"VALUE_TYPE=%s\"", classOf[Address].getName))
.setSchema("PUBLIC")).getAll
cache.query(new SqlFieldsQuery("INSERT INTO Person(id,street, zip)
VALUES(?,?, ?)").setArgs(1L.asInstanceOf[JLong],"Jameco",
"04074").setSchema("PUBLIC")).getAll
cache.query(new SqlFieldsQuery("INSERT INTO Person(id,street, zip)
VALUES(?,?, ?)").setArgs(2L.asInstanceOf[JLong],"Bremar road",
"520003").setSchema("PUBLIC")).getAll
cache.query(new SqlFieldsQuery("INSERT INTO Person(id,street, zip)
VALUES(?,?, ?)").setArgs(3L.asInstanceOf[JLong],"orange road",
"1234").setSchema("PUBLIC")).getAll
System.out.format(">>> Data Inserted into Cache [%s].\n", CACHE_NAME)
val data=cache.query(new SqlFieldsQuery("select * from
Person").setSchema("PUBLIC")).getAll
println(data.toString)
}
def sparkReadIgniteWithThinClient(implicit spark: SparkSession)={
val df = spark.read
.format("jdbc")
.option("url", "jdbc:ignite:thin://18.206.247.40")
.option("fetchsize",100)
//.option("driver", "org.apache.ignite.IgniteJdbcDriver")
.option("dbtable", "Person").load()
df.printSchema()
df.createOrReplaceTempView("test")
spark.sql("select * from test where id=1").show(10)
spark.sql("select 4,'blah',124232").show(10)
}
def sparkWriteIgniteWithThinClient(implicit spark: SparkSession)={
import java.sql.DriverManager
val connection =
DriverManager.getConnection("jdbc:ignite:thin://18.206.247.40")
import java.util.Properties
val connectionProperties = new Properties()
connectionProperties.put("url", "jdbc:ignite:thin://18.206.247.40")
spark.sql("select 4 as ID,'blah' as STREET,124232 as
ZIP").write.mode(SaveMode.Append).jdbc("jdbc:ignite:thin://18.206.247.40",
"Person",connectionProperties)
spark.read
.format("jdbc")
.option("url", "jdbc:ignite:thin://18.206.247.40")
.option("fetchsize",100)
.option("dbtable", "Person").load().show(10,false)
}
def writeJSonToIgniteUsingSpark(implicit spark: SparkSession): Unit = {
val ignite = Ignition.start(CONFIG)
//Load content of json file to data frame.
val personsDataFrame = spark.read.json(
resolveIgnitePath("/Users/kalit_000/Downloads/designing-event-driven-applications-apache-kafka-ecosystem/05/demos/kafka-streams-after/ApacheIgnitePoc/src/main/resources/person.json").getAbsolutePath)
println()
println("Json file content:")
println()
//Printing content of json file to console.
personsDataFrame.show()
println()
println("Writing Data Frame to Ignite:")
println()
//Writing content of data frame to Ignite.
personsDataFrame.write
.format(FORMAT_IGNITE)
.mode(org.apache.spark.sql.SaveMode.Append)
.option(OPTION_CONFIG_FILE, CONFIG)
.option(OPTION_TABLE, "json_person")
.option(OPTION_CREATE_TABLE_PRIMARY_KEY_FIELDS, "id")
.option(OPTION_CREATE_TABLE_PARAMETERS, "template=replicated")
.save()
println("Done!")
println()
println("Reading data from Ignite table:")
println()
val cache = ignite.cache[Any, Any](CACHE_NAME)
//Reading saved data from Ignite.
val data = cache.query(new SqlFieldsQuery("SELECT id, name,
department FROM json_person")).getAll
println(data.toString)
//data.foreach { row ⇒ println(row.mkString("[", ", ", "]")) }
}
def readIgniteUsingSpark(implicit spark: SparkSession) = {
val json_person = spark.read
.format(FORMAT_IGNITE)
.option(OPTION_CONFIG_FILE, CONFIG)
.option(OPTION_TABLE, "json_person")
.load()
println()
println("Data frame content:json_person")
println()
//Printing content of data frame to console.
json_person.show()
}
def readThinClientTableUsingSpark(implicit spark: SparkSession) = {
val personDataFrame = spark.read
.format(FORMAT_IGNITE)
.option(OPTION_CONFIG_FILE, CONFIG)
.option(OPTION_TABLE, "person")
.load()
println()
println("Data frame thin connection content:person")
println()
//Printing content of data frame to console.
personDataFrame.show()
}
def main(args: Array[String]): Unit = {
println()
println("Step 1 setupExampleData:")
println()
setupExampleData
println()
println("Step 2 createSparkSession:")
println()
//Creating spark session.
implicit val spark = SparkSession.builder()
.appName("Spark Ignite data sources example")
.master("local")
.config("spark.executor.instances", "2")
.getOrCreate()
// Adjust the logger to exclude the logs of no interest.
Logger.getRootLogger.setLevel(Level.ERROR)
Logger.getLogger("org.apache.ignite").setLevel(Level.INFO)
println()
println("Step 3 ReadIgniteWithThinClient of Step1 Data:")
println()
sparkReadIgniteWithThinClient(spark)
println()
println("Step 4 sparkWriteIgniteWithThinClient of Step1 Data:")
println()
sparkWriteIgniteWithThinClient(spark)
println()
println("Step 5 writeJSonToIgniteUsingSpark Using Spark:")
println()
writeJSonToIgniteUsingSpark(spark)
println()
println("Step 6 readIgniteUsingSpark Using Spark:")
println()
readIgniteUsingSpark(spark)
println()
println("Step 7 readThinClientTableUsingSpark Using Spark:")
println()
readThinClientTableUsingSpark(spark)
spark.stop()
}
}
example-default.xml
<?xml version="1.0" encoding="UTF-8"?>
<!--
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.
-->
<!--
Ignite configuration with all defaults and enabled p2p deployment
and enabled events.
-->
<beans xmlns="http://www.springframework.org/schema/beans";
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance";
xmlns:util="http://www.springframework.org/schema/util";
xsi:schemaLocation="
http://www.springframework.org/schema/beans
http://www.springframework.org/schema/beans/spring-beans.xsd
http://www.springframework.org/schema/util
http://www.springframework.org/schema/util/spring-util.xsd";>
<bean abstract="true" id="ignite.cfg"
class="org.apache.ignite.configuration.IgniteConfiguration">
<!-- Set to true to enable distributed class loading for
examples, default is false. -->
<property name="peerClassLoadingEnabled" value="true"/>
<!-- Enable task execution events for examples. -->
<property name="includeEventTypes">
<list>
<!--Task execution events-->
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_TASK_STARTED"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_TASK_FINISHED"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_TASK_FAILED"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_TASK_TIMEDOUT"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_TASK_SESSION_ATTR_SET"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_TASK_REDUCED"/>
<!--Cache events-->
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_CACHE_OBJECT_PUT"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_CACHE_OBJECT_READ"/>
<util:constant
static-field="org.apache.ignite.events.EventType.EVT_CACHE_OBJECT_REMOVED"/>
</list>
</property>
<!-- Explicitly configure TCP discovery SPI to provide list of
initial nodes. -->
<property name="discoverySpi">
<bean class="org.apache.ignite.spi.discovery.tcp.TcpDiscoverySpi">
<property name="ipFinder">
<!--
Ignite provides several options for automatic
discovery that can be used
instead os static IP based discovery. For
information on all options refer
to our documentation:
http://apacheignite.readme.io/docs/cluster-config
-->
<!-- Uncomment static IP finder to enable
static-based discovery of initial nodes. -->
<!--<bean
class="org.apache.ignite.spi.discovery.tcp.ipfinder.vm.TcpDiscoveryVmIpFinder">-->
<bean
class="org.apache.ignite.spi.discovery.tcp.ipfinder.multicast.TcpDiscoveryMulticastIpFinder">
<property name="addresses">
<list>
<!-- In distributed environment,
replace with actual host IP address. -->
<value>18.206.247.40:10800</value>
</list>
</property>
</bean>
</property>
</bean>
</property>
</bean>
</beans>
Thanks
Sri
On Fri, Oct 18, 2019 at 9:23 AM sri hari kali charan Tummala <
[email protected]> wrote:
> do you mean communication ports 47100-47200 as mentioned (
> https://www.gridgain.com/docs/8.7.6//installation-guide/manual-install-on-ec2)
> ? bare in mind I am running my spark job outside ignite ec2 box (MAC PC).
>
> which option is right in my default.xml file?
>
> Option 1:-
>
> <property name="addresses">
> <list>
> <!-- In distributed environment, replace with
> actual host IP address. -->
> <value>3.88.248.113:4
> <http://3.88.248.113:10800/>7100..47200</value>
> </list>
> </property>
>
>
> Option 2:-
>
> <property name="addresses">
> <list>
> <!-- In distributed environment, replace with
> actual host IP address. -->
> <value>3.88.248.113:4
> <http://3.88.248.113:10800/>7500..47600</value>
> </list>
> </property>
>
>
> Option 3:-
>
> <property name="addresses">
> <list>
> <!-- In distributed environment, replace with
> actual host IP address. -->
> <value>3.88.248.113
> <http://3.88.248.113:10800/></value>
> </list>
> </property>
>
>
>
> Thanks
>
> On Fri, Oct 18, 2019 at 9:18 AM sri hari kali charan Tummala <
> [email protected]> wrote:
>
>> Hi Stephen ,
>>
>> do you mean 3.88.248.113: <http://3.88.248.113:10800/>47500..47700
>> something like this? or just public ip 3.88.248.113
>> <http://3.88.248.113:10800/> I tried all the possibilities none of them
>> are getting connected.
>>
>> Thanks
>> Sri
>>
>> On Fri, Oct 18, 2019 at 6:02 AM Stephen Darlington <
>> [email protected]> wrote:
>>
>>> You’re trying to connect a thick client (the Spark integration) to the
>>> thin client port (10800). Your example-default.xml file needs to have the
>>> same configuration as your server node(s).
>>>
>>> Regards,
>>> Stephen
>>>
>>> On 17 Oct 2019, at 18:12, sri hari kali charan Tummala <
>>> [email protected]> wrote:
>>>
>>> Hi Community,
>>>
>>> I am trying to read and write into the Ignite cluster using apache-spark
>>> I am able to do that using JDBC thin client but not native method as
>>> mentioned in several spark + ignite examples.
>>>
>>> Right now all the spark + ignite examples launch a local ignite cluster
>>> but I want my code connecting to already existing cluster (client).
>>>
>>> Question:-
>>> *How to pass Ignite connection ip and port (10800) 10800 in
>>> example-default.xml ?*
>>>
>>> Error:-
>>> *TcpDiscoverySpi: Failed to connect to any address from IP finder (will
>>> retry to join topology every 2000 ms; change 'reconnectDelay' to configure
>>> the frequency of retries): [/3.88.248.113:10800
>>> <http://3.88.248.113:10800/>]*
>>>
>>> Working (Spark + Ignite using JDBC):-
>>>
>>> val df = spark.read
>>> .format("jdbc")
>>> .option("url", "jdbc:ignite:thin://3.88.248.113")
>>> .option("fetchsize",100)
>>> //.option("driver", "org.apache.ignite.IgniteJdbcDriver")
>>> .option("dbtable", "Person").load()
>>>
>>> df.printSchema()
>>>
>>> df.createOrReplaceTempView("test")
>>>
>>> spark.sql("select * from test where id=1").show(10)
>>>
>>> spark.sql("select 4,'blah',124232").show(10)
>>>
>>> import java.sql.DriverManager
>>> val connection =
>>> DriverManager.getConnection("jdbc:ignite:thin://3.88.248.113")
>>>
>>> import java.util.Properties
>>> val connectionProperties = new Properties()
>>>
>>> connectionProperties.put("url", "jdbc:ignite:thin://3.88.248.113")
>>>
>>> spark.sql("select 4 as ID,'blah' as STREET,124232 as
>>> ZIP").write.mode(SaveMode.Append).jdbc("jdbc:ignite:thin://3.88.248.113",
>>> "Person",connectionProperties)
>>>
>>> spark.read
>>> .format("jdbc")
>>> .option("url", "jdbc:ignite:thin://3.88.248.113")
>>> .option("fetchsize",100)
>>> .option("dbtable", "Person").load().show(10,false)
>>>
>>>
>>> Not Working requires a CONFIG file which is example-default.xml:-
>>>
>>> val igniteDF = spark.read
>>> .format(FORMAT_IGNITE) //Data source type.
>>> .option(OPTION_TABLE, "person") //Table to read.
>>> .option(OPTION_CONFIG_FILE, CONFIG) //Ignite config.
>>> .load()
>>> .filter(col("id") >= 2) //Filter clause.
>>> .filter(col("name") like "%J%") //Another filter clause.
>>>
>>>
>>> Full Code:- (sparkDSLExample) function fails to connect ignite cluster
>>> which I already have
>>>
>>> package com.ignite.examples.spark
>>>
>>> import com.ignite.examples.model.Address
>>> import org.apache.ignite.{Ignite, Ignition}
>>> import org.apache.ignite.cache.query.SqlFieldsQuery
>>> import org.apache.ignite.client.{ClientCache, IgniteClient}
>>> import org.apache.ignite.configuration.{CacheConfiguration,
>>> ClientConfiguration}
>>> import java.lang.{Long => JLong, String => JString}
>>>
>>> import org.apache.ignite.cache.query.SqlFieldsQuery
>>> import org.apache.ignite.spark.IgniteDataFrameSettings.{FORMAT_IGNITE,
>>> OPTION_CONFIG_FILE, OPTION_TABLE}
>>> import org.apache.log4j.{Level, Logger}
>>> import org.apache.spark.sql.{SaveMode, SparkSession}
>>> import org.apache.spark.sql.functions.col
>>>
>>> object SparkClientConnectionTest {
>>>
>>> private val CACHE_NAME = "SparkCache"
>>>
>>> private val CONFIG =
>>> "/Users/kalit_000/Downloads/designing-event-driven-applications-apache-kafka-ecosystem/05/demos/kafka-streams-after/ApacheIgnitePoc/src/main/scala/com/ignite/examples/config/example-ignite.xml"
>>>
>>> def setupExampleData = {
>>>
>>> val cfg2 = new ClientConfiguration().setAddresses("3.88.248.113:10800")
>>> val igniteClient:IgniteClient = Ignition.startClient(cfg2)
>>>
>>> System.out.format(">>> Created cache [%s].\n", CACHE_NAME)
>>>
>>> val cache:ClientCache[Integer, Address] =
>>> igniteClient.getOrCreateCache(CACHE_NAME)
>>>
>>> cache.query(new SqlFieldsQuery(String.format("DROP TABLE IF EXISTS
>>> Person"))
>>> .setSchema("PUBLIC")).getAll
>>>
>>> cache.query(new SqlFieldsQuery(String.format("CREATE TABLE IF NOT
>>> EXISTS Person (id LONG,street varchar, zip VARCHAR, PRIMARY KEY (id) ) WITH
>>> \"VALUE_TYPE=%s\"", classOf[Address].getName))
>>> .setSchema("PUBLIC")).getAll
>>>
>>> cache.query(new SqlFieldsQuery("INSERT INTO Person(id,street, zip)
>>> VALUES(?,?, ?)").setArgs(1L.asInstanceOf[JLong],"Jameco",
>>> "04074").setSchema("PUBLIC")).getAll
>>> cache.query(new SqlFieldsQuery("INSERT INTO Person(id,street, zip)
>>> VALUES(?,?, ?)").setArgs(2L.asInstanceOf[JLong],"Bremar road",
>>> "520003").setSchema("PUBLIC")).getAll
>>> cache.query(new SqlFieldsQuery("INSERT INTO Person(id,street, zip)
>>> VALUES(?,?, ?)").setArgs(3L.asInstanceOf[JLong],"orange road",
>>> "1234").setSchema("PUBLIC")).getAll
>>>
>>> System.out.format(">>> Data Inserted into Cache [%s].\n", CACHE_NAME)
>>>
>>> val data=cache.query(new SqlFieldsQuery("select * from
>>> Person").setSchema("PUBLIC")).getAll
>>>
>>> println(data.toString)
>>> }
>>>
>>> def sparkDSLExample(implicit spark: SparkSession): Unit = {
>>> println("Querying using Spark DSL.")
>>> println
>>>
>>>
>>> val igniteDF = spark.read
>>> .format(FORMAT_IGNITE) //Data source type.
>>> .option(OPTION_TABLE, "person") //Table to read.
>>> .option(OPTION_CONFIG_FILE, CONFIG) //Ignite config.
>>> .load()
>>> .filter(col("id") >= 2) //Filter clause.
>>> .filter(col("name") like "%J%") //Another filter clause.
>>>
>>> println("Data frame schema:")
>>>
>>> igniteDF.printSchema() //Printing query schema to console.
>>>
>>> println("Data frame content:")
>>>
>>> igniteDF.show() //Printing query results to console.
>>> }
>>>
>>>
>>> def main(args: Array[String]): Unit = {
>>>
>>> setupExampleData
>>>
>>> //Creating spark session.
>>> implicit val spark = SparkSession.builder()
>>> .appName("Spark Ignite data sources example")
>>> .master("local")
>>> .config("spark.executor.instances", "2")
>>> .getOrCreate()
>>>
>>> // Adjust the logger to exclude the logs of no interest.
>>> Logger.getRootLogger.setLevel(Level.ERROR)
>>> Logger.getLogger("org.apache.ignite").setLevel(Level.INFO)
>>>
>>> //sparkDSLExample
>>>
>>>
>>> val df = spark.read
>>> .format("jdbc")
>>> .option("url", "jdbc:ignite:thin://3.88.248.113")
>>> .option("fetchsize",100)
>>> //.option("driver", "org.apache.ignite.IgniteJdbcDriver")
>>> .option("dbtable", "Person").load()
>>>
>>> df.printSchema()
>>>
>>> df.createOrReplaceTempView("test")
>>>
>>> spark.sql("select * from test where id=1").show(10)
>>>
>>> spark.sql("select 4,'blah',124232").show(10)
>>>
>>> import java.sql.DriverManager
>>> val connection =
>>> DriverManager.getConnection("jdbc:ignite:thin://3.88.248.113")
>>>
>>> import java.util.Properties
>>> val connectionProperties = new Properties()
>>>
>>> connectionProperties.put("url", "jdbc:ignite:thin://3.88.248.113")
>>>
>>> spark.sql("select 4 as ID,'blah' as STREET,124232 as
>>> ZIP").write.mode(SaveMode.Append).jdbc("jdbc:ignite:thin://3.88.248.113",
>>> "Person",connectionProperties)
>>>
>>> spark.read
>>> .format("jdbc")
>>> .option("url", "jdbc:ignite:thin://3.88.248.113")
>>> .option("fetchsize",100)
>>> .option("dbtable", "Person").load().show(10,false)
>>>
>>> }
>>>
>>> }
>>>
>>>
>>> example-default.xml:-
>>>
>>> <?xml version="1.0" encoding="UTF-8"?>
>>>
>>> <!--
>>> 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.
>>> -->
>>>
>>> <!--
>>> Ignite configuration with all defaults and enabled p2p deployment and
>>> enabled events.
>>> -->
>>> <beans xmlns="http://www.springframework.org/schema/beans";
>>> xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance";
>>> xmlns:util="http://www.springframework.org/schema/util";
>>> xsi:schemaLocation="
>>> http://www.springframework.org/schema/beans
>>> http://www.springframework.org/schema/beans/spring-beans.xsd
>>> http://www.springframework.org/schema/util
>>> http://www.springframework.org/schema/util/spring-util.xsd";>
>>> <bean abstract="true" id="ignite.cfg"
>>> class="org.apache.ignite.configuration.IgniteConfiguration">
>>> <!-- Set to true to enable distributed class loading for examples,
>>> default is false. -->
>>> <property name="peerClassLoadingEnabled" value="true"/>
>>>
>>> <!-- Enable task execution events for examples. -->
>>> <property name="includeEventTypes">
>>> <list>
>>> <!--Task execution events-->
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_TASK_STARTED"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_TASK_FINISHED"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_TASK_FAILED"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_TASK_TIMEDOUT"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_TASK_SESSION_ATTR_SET"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_TASK_REDUCED"/>
>>>
>>> <!--Cache events-->
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_CACHE_OBJECT_PUT"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_CACHE_OBJECT_READ"/>
>>> <util:constant
>>> static-field="org.apache.ignite.events.EventType.EVT_CACHE_OBJECT_REMOVED"/>
>>> </list>
>>> </property>
>>>
>>> <!-- Explicitly configure TCP discovery SPI to provide list of
>>> initial nodes. -->
>>> <property name="discoverySpi">
>>> <bean
>>> class="org.apache.ignite.spi.discovery.tcp.TcpDiscoverySpi">
>>> <property name="ipFinder">
>>> <!--
>>> Ignite provides several options for automatic
>>> discovery that can be used
>>> instead os static IP based discovery. For
>>> information on all options refer
>>> to our documentation:
>>> http://apacheignite.readme.io/docs/cluster-config
>>> -->
>>> <!-- Uncomment static IP finder to enable static-based
>>> discovery of initial nodes. -->
>>> <!--<bean
>>> class="org.apache.ignite.spi.discovery.tcp.ipfinder.vm.TcpDiscoveryVmIpFinder">-->
>>> <bean
>>> class="org.apache.ignite.spi.discovery.tcp.ipfinder.multicast.TcpDiscoveryMulticastIpFinder">
>>> <property name="addresses">
>>> <list>
>>> <!-- In distributed environment, replace
>>> with actual host IP address. -->
>>> <value>3.88.248.113:10800</value>
>>> </list>
>>> </property>
>>> </bean>
>>> </property>
>>> </bean>
>>> </property>
>>> </bean>
>>> </beans>
>>>
>>>
>>>
>>>
>>> --
>>> Thanks & Regards
>>> Sri Tummala
>>>
>>>
>>>
>>>
>>
>> --
>> Thanks & Regards
>> Sri Tummala
>>
>>
>
> --
> Thanks & Regards
> Sri Tummala
>
>
--
Thanks & Regards
Sri Tummala
