mustafaakin

$ eval $(docker-machine env --swarm mhs-demo0-do)
$ docker info
Containers: 3
Images: 2
Role: primary
Strategy: spread
Filters: health, port, dependency, affinity, constraint
Nodes: 2
 mhs-demo0-do: 188.166.113.176:2376
  └ Containers: 2

mustafaakin

docker run --name iperf_host -d -ti --net host \
    --env="constraint:node==mhs-demo0-do" \
    mustafaakin/alpine-iperf iperf -s 

# Wait a little
sleep 1

for run in {1..5}; do 
    docker run --net host --env="constraint:node==mhs-demo1-do" -ti \
    mustafaakin/alpine-iperf \

mustafaakin

docker network create -d overlay mynet
docker run --name iperf_overlay -d -ti --net mynet \
    --env="constraint:node==mhs-demo0-do" \
    mustafaakin/alpine-iperf iperf -s 

# Wait a little
sleep 1

IP=$(docker inspect -f "{ { .NetworkSettings.Networks.mynet.IPAddress }}" iperf_overlay)
for run in {1..5}; do 

mustafaakin

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple3;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.timestamps.AscendingTimestampExtractor;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.java.StreamTableEnvironment;
import org.apache.flink.types.Row;

mustafaakin

SELECT 
  room, 
  TUMBLE_END(rowtime, INTERVAL ‘10’ SECOND), 
  AVG(temperature) AS avgTemp 
FROM sensors 
GROUP BY 
  TUMBLE(rowtime, INTERVAL ‘10’ SECOND), 
  room

mustafaakin

// A data stream, in reality it would be Kafka, Kinesis or other streams
DataStream<String> text = env.socketTextStream("localhost", port, "\n");

// Format the streaming data into a row format
DataStream<Tuple3<String, Double, Time>> dataset = text
        .map(mapFunction)
        .assignTimestampsAndWatermarks(extractor); 

// Register it so we can refer it as 'sensors' in SQL
tableEnv.registerDataStream("sensors", dataset, "room, temperature, creationDate, rowtime.rowtime");

mustafaakin

hyperkit -A -m 512M -s 0:0,hostbridge \
  -s 31,lpc \
  -l com1,stdio \
  -s 1:0,ahci-hd,file://$(pwd)/$QCOW2,format=qcow  \
  -s 5,ahci-cd,$(pwd)/seed.img \
  -f kexec,$KERNEL,$INITRD,$CMDLIN
mirage_block_open: block_config = file:///Users/mustafa/Downloads/xenial-server-cloudimg-amd64-disk1.qcow2 and qcow_config = None and stats_config = None
                                                                                                                                                         hyperkit: [INFO] Resized file to 32768 clusters (4194304 sectors)
                                                              hyperkit: [INFO] image has 0 free sectors and 32764 used sectors
                                                                                                                              mirage_block_open: block_config = file:///Users/mustafa/Downloads/xenial-server-cloudimg-amd64-disk1.qcow2 and qcow_config = None and stats_config = None returning 0

mustafaakin

<dependency>
    <groupId>org.apache.parquet</groupId>
    <artifactId>parquet-common</artifactId>
    <version>1.9.0</version>
</dependency>

<dependency>
    <groupId>org.apache.parquet</groupId>
    <artifactId>parquet-avro</artifactId>
    <version>1.9.0</version>

mustafaakin

Configuration conf = new Configuration();
Path p = new Path("data.parquet"); // This is not java.nio.file.Path     

ParquetWriter<FlowLogs> writer = AvroParquetWriter.<FlowLog>builder(p)
    .withSchema(ReflectData.AllowNull.get().getSchema(FlowLog.class))
    .withDataModel(ReflectData.get())
    .withConf(conf)
    .withCompressionCodec(CompressionCodecName.SNAPPY)
    .withWriteMode(Mode.OVERWRITE)
    .build();

mustafaakin

SchemaBuilder.RecordBuilder<Schema> builder = SchemaBuilder
        .record("flow_logs").namespace("com.opsgenie");

schema = builder.fields()
    .name("version").type().intType().intDefault(0)
    .name("account").type().stringType().stringDefault("")
    .name("interfaceId").type().stringType().stringDefault("")
    .name("sourceAddress").type().stringType().stringDefault("")
    // continues for remaining 10 fields..