1. Lattafa Opulent Oud (100 ml) — loud amber-oud, smoky-sweet
   ₹1,805–2,200 on Flipkart.
2. Lattafa Asad (100 ml) — sweet/spicy amber with strong projection
   ₹1,499 on Fragstalk.
3. Lattafa Raghba Wood Intense (100 ml) — syrupy vanilla-oud wood bomb
   ₹1,349 on Fragstalk; ~₹1,789 on Flipkart.
4. Al Haramain Detour Noir (100 ml) — creamy almond/amber, room-filling
   ₹1,499 on Fragstalk; ₹2,499 at Perfume Network.
5. Paris Corner Killer Oud – Death by Oud (100 ml) — leathery, smoky, thick oud
   ₹1,949 at PerfumePalace; ~₹1,999 on Fragstalk.
6. Lattafa Fakhar Gold Extrait (100 ml) — dense fruity-amber, very tenacious
   ₹2,099 on AAR Fragrances / Fragstalk.
7. Lattafa Najdia (100 ml) — bright aquatic-amber with “beast” sillage on clothes
   ₹1,588–2,000 on Flipkart; ~₹1,570 on Fragstalk.
8. Fragrance World Barakkat Rouge 540 (100 ml) — cotton-candy amber/woody “BR540” style, huge trail
   ₹1,599–1,649 (Fragstalk / PerfumePalace).
9. Ard Al Zaafaran Oud 24 Hours (100 ml) — chocolaty amber-oud, notorious projector
   ₹1,349 on Fragstalk; ~₹1,686 on Flipkart.
10. Lattafa Oud Mood (100 ml) — resinous smoky-sweet oud amber, “fills a room”
    ₹1,499 on Fragstalk; ~₹2,000 on Flipkart / ~₹1,799 on Amazon.

Quick tips:

• For true “nuclear,” spray on clothes (test fabric first) and limit to 2–3 sprays to avoid going anosmic or choking a room.

Performance Ranking

1. Enigma – Green Essence (Inspired by Polo Green)

• Similarity: Very close to vintage Polo Green (pine, leather, tobacco, oakmoss).
• Projection: Strong for first 2 hours, noticeable bubble around you.
• Longevity: 6–7 hours on skin, longer on clothes.
• Best choice if you want power + authenticity.

2. Master Cologne – P0L0 Green Inspired Version

• Similarity: Slightly fresher/modernized, but keeps the green-leather backbone.
• Projection: Strong for 1–2 hours, then moderate.
• Longevity: 5–6 hours, surprisingly good for the price.
• Best budget “beast mode” pick.

3. Vogue Roots – Inspired by Polo Green

• Similarity: Green-woody, more wearable and a bit smoother.
• Projection: Moderate for 1.5–2 hours.
• Longevity: Around 5 hours.
• Balanced choice if you want something wearable daily.

4. Perfume Clones – Polo Green

• Similarity: Recognizable as Polo Green but slightly synthetic.
• Projection: Moderate for 1 hour.
• Longevity: 3–4 hours.
• Only if you want the cheapest possible option.

Best overall clone in India: Enigma Green Essence
Best budget beast mode: Master Cologne Polo Green
Most wearable daily version: Vogue Roots Inspired

—

 Beast Mode Arabic Clones

1. Lattafa Qaeed / Qae’ed

Clone of: Initio Blessed Baraka

Profile: Spicy, woody, smoky with vanilla & oud.

Performance: Absolute powerhouse, 10–12+ hrs with room-filling projection.

—

2. Paris Corner Emir Wild & Tobacco

Clone of: Tom Ford Tobacco Oud

Profile: Dark tobacco, oud, spice, resinous.

Performance: Extremely strong, heavy winter scent, nuclear sillage.

—

3. Paris Corner Charuto Tobacco Vanille

Clone of: Tom Ford Tobacco Vanille

Profile: Sweet tobacco, vanilla, dried fruits, cocoa.

Performance: Thick, heavy, 8–10+ hrs easily. One of the strongest TV clones.

—

4. Lattafa Asad

Clone of: Dior Sauvage Elixir

Profile: Spicy lavender, amber, woods, warm masculine.

Performance: Projects like crazy, easily 9–12 hrs.

—

5. Paris Corner Pendora Scents Supremacy Not Only Intense (SNII by Afnan also counts)

Clone of: Creed Aventus with darker smoky twist.

Profile: Fruity pineapple, smoke, ambergris.

Performance: Strong projection, beast-mode longevity.

—

6. Lattafa Najdia Intense

Clone of: Rasasi Hawas / Invictus Aqua DNA

Profile: Aquatic, citrus, bubblegummy sweet freshie.

Performance: Strong summer beast, lasts 8–10 hrs, projects hard.

—

7. Paris Corner Emir Rifaaqat Adorn

Clone of: YSL Tuxedo

Profile: Patchouli, amber, rose, vanilla.

Performance: Heavy, elegant, pushes very strong for hours.

—

8. Ministry of Oud Greatest (Paris Corner)

Clone of: Initio Oud for Greatness

Profile: Oud, saffron, lavender, incense.

Performance: Nuclear projection, lasts 12+ hrs on skin, days on clothes.

—

If you liked Atlas for its salty-aquatic but nuclear projection, I’d suggest checking Najdia Intense (Lattafa) or Asad for something equally loud but different DNA.

1. Paris Corner – Emir Wild & Tobacco

Clone of: Tom Ford Tobacco Vanille

Profile: Spicy vanilla, dried fruits, sweet tobacco.

Performance: 10+ hours, strong projection.

2. Paris Corner – Emir Oud & Vanille

Clone of: Van Cleef & Arpels Bois d’Oud & Vanille

Profile: Dark vanilla, resinous woods, balsamic richness.

Performance: Beast, especially in cold weather.

3. Paris Corner – Charuto Tobacco Vanille

Clone of: Tom Ford Tobacco Vanille

Profile: Heavy tobacco, cinnamon, cacao, and vanilla sweetness.

Performance: Monster sillage & longevity.

4. Lattafa – Qaed Al Fursan Unlimited

Clone of: Initio Oud for Greatness (with extra vanilla twist)

Profile: Woody-oud base with sweet gourmand vanilla undertone.

Performance: Nuclear longevity, loud projection.

5. Lattafa – Asad (Original or Zanzibar edition)

Clone of: Dior Sauvage Elixir (OG Asad) / YSL Tuxedo (Zanzibar)

Profile: Not pure gourmand, but spicy-sweet tonka and vanilla nuances.

Performance: Beast.

6. Afnan – 9PM

Clone of: Jean Paul Gaultier Ultra Male

Profile: Sweet bubblegum-like pear, cinnamon, vanilla, and tonka bean.

Performance: Party beast, projects like crazy.

7. Fragrance World – After Effect

Clone of: Initio Side Effect

Profile: Boozy rum, tobacco, vanilla, and cinnamon – a true gourmand.

Performance: Beast in cold weather.

8. Paris Corner – North Stag Expressions (Esp. “III” and “IV”)

Clone of: Xerjoff Italica / Kilian Angels’ Share

Profile: Almond, milk, caramel (Italica) or boozy cinnamon vanilla (Angels’ Share).

Performance: Long-lasting gourmand bombs.

—

Absolute Monsters if You Want “Sugar Overload”

Lattafa – Khamrah → Clone of Kilian Angels’ Share (dates, praline, vanilla, boozy cinnamon) – viral for being a beast gourmand.

Paris Corner – Khamrah Qahwa → Adds coffee to the Khamrah DNA = sweet, creamy gourmand.

Lattafa – Oud for Glory Bade’e Al Oud Amethyst → Clone of Initio Psychedelic Love (vanilla + heliotrope + almond).

Kafka Consumer Threads: Ensure each Kafka consumer thread is handling a separate partition to avoid concurrent processing issues.

Task Executor: Properly configure the task executor to manage the concurrency.

BlockingQueue: Use a thread-safe queue to manage items between the Kafka listener and the batch job.

Stateless Components: Ensure the ItemProcessor and ItemWriter are either stateless or handle state in a thread-safe manner.By following these guidelines, you can achieve a thread-safe implementation of a parallelized Kafka reader in a Spring Batch application.

The @KafkaListener method listen is automatically called by Spring Kafka whenever a message is received on the specified topic. The Spring Kafka framework handles this, so you don’t need to explicitly call the listen method. This is part of the declarative programming model provided by Spring Kafka.

Here’s a detailed explanation of how this works:

How @KafkaListener Works

• Annotation: The @KafkaListener annotation on the listen method tells Spring to create a message listener for the specified Kafka topic.
• Message Reception: When a message is received on the topic, the KafkaListener container automatically calls the listen method and passes the message to it.
• Thread-Safety: Since the BlockingQueue is thread-safe, it can handle concurrent access from multiple listener threads.

Here is a refined version of the KafkaItemReader for clarity:@Component public class KafkaItemReader implements ItemReader<String> { private final BlockingQueue<String> queue = new LinkedBlockingQueue<>(); @KafkaListener(topics = "your-topic", groupId = "batch-group") public void listen(ConsumerRecord<String, String> record) { queue.offer(record.value()); } @Override public String read() throws Exception { return queue.poll(100, TimeUnit.MILLISECONDS); } }

Steps to Ensure Thread Safety and Correct Execution

1. KafkaListener: The @KafkaListener annotation is configured to listen to messages from the Kafka topic. When messages arrive, they are automatically passed to the listen method.
2. BlockingQueue: The BlockingQueue is used to store messages. It handles concurrent access from multiple threads safely.
3. Read Method: The read method is called by the Spring Batch framework to read items for processing. It polls the BlockingQueue for new messages.

Complete Example

Here’s a complete example tying all components together:

Kafka Configuration

@Configuration public class KafkaConsumerConfig { @Value("${kafka.bootstrap-servers}") private String bootstrapServers; @Bean public Map<String, Object> consumerConfigs() { Map<String, Object> props = new HashMap<>(); props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers); props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class); props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class); props.put(ConsumerConfig.GROUP_ID_CONFIG, "batch-group"); return props; } @Bean public ConsumerFactory<String, String> consumerFactory() { return new DefaultKafkaConsumerFactory<>(consumerConfigs()); } @Bean public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() { ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>(); factory.setConsumerFactory(consumerFactory()); factory.setConcurrency(3); // Number of threads return factory; } }

Batch Configuration

@Configuration @EnableBatchProcessing public class BatchConfig { @Autowired private JobBuilderFactory jobBuilderFactory; @Autowired private StepBuilderFactory stepBuilderFactory; @Autowired private KafkaItemReader kafkaItemReader; @Bean public Job kafkaJob() { return jobBuilderFactory.get("kafkaJob") .start(step1()) .build(); } @Bean public Step step1() { return stepBuilderFactory.get("step1") .<String, String>chunk(10) .reader(kafkaItemReader) .processor(processor()) .writer(writer()) .taskExecutor(taskExecutor()) // Enable parallel processing .build(); } @Bean public ItemProcessor<String, String> processor() { return item -> { // Process the item return item; }; } @Bean public ItemWriter<String> writer() { return items -> { // Write the items }; } @Bean public TaskExecutor taskExecutor() { SimpleAsyncTaskExecutor taskExecutor = new SimpleAsyncTaskExecutor(); taskExecutor.setConcurrencyLimit(10); // Number of concurrent threads return taskExecutor; } }

Kafka Item Reader

@Component public class KafkaItemReader implements ItemReader<String> { private final BlockingQueue<String> queue = new LinkedBlockingQueue<>(); @KafkaListener(topics = "your-topic", groupId = "batch-group") public void listen(ConsumerRecord<String, String> record) { queue.offer(record.value()); } @Override public String read() throws Exception { return queue.poll(100, TimeUnit.MILLISECONDS); // Adjust timeout as needed } }

Application Properties

kafka.bootstrap-servers=localhost:9092 spring.kafka.consumer.group-id=batch-group spring.kafka.consumer.auto-offset-reset=earliest

This setup ensures that your Kafka messages are processed in a thread-safe manner, leveraging Spring Kafka’s automatic message listener mechanism and Spring Batch’s parallel processing capabilities.

• Deploying Splunk
  • Deployment Models
    • Splunk has a Cloud Deployment and On Premise deployment options.
    • Splunk Data Pipeline
      • Input
        • Load forwarded data, uploaded data, files etc
      • Parseing
        • Examine the data and adds metadata
      • Indexing
        • Divides the data into events and writes the data into disks in “buckets”.
      • Searching
        • User interaction with the data
    • Splunk Installations
      • Universal Forwarder
        • This is a lightweight splunk agent.
      • Splunk Enterprise Installation
        • This has all the splunk components.
    • Components that make up the splunk
      • Forwarder
      • Heavy Forwarder
      • Search Head
      • Deployment server
      • Master Cluster Node
      • License Server
      • Indexer
      • Deployer
  • Data Storage in disk
    • Index
      • Repository for splunk data
      • Raw data into events and stores then into index buckets with metadata
      • Default index that comes with splunk is called main and also has a _internal that stores the internal logs.
    • Event
      • Single row of data is called event
      • Events have fields which are key value pairs.
      • Splunk adds default fields to all events.
        • Timestamp
        • Host
        • Source
        • Source Type
      • Data is stored into directories called buckets based on age. There are 6 default buckets
        • Hot – Read/Write
        • Warm – Only Read rolled from Hot
        • Cold – Moved to a different location. Data rolled from Warm
        • Frozen – Deleted or Archived data. Data rolled from Cold.
        • Thawed – The data that is restored from Frozen
        • Fished
      • Different configs to be done on bucket
        • Retirement Policy
        • Archive and Restore from archive
        • Backup Data
        • Configure Index Size
        • Partition Index Data
  • Licensing
    • License data injested per data not data stored.
    • Daily indexing volume is measured from midnight to midnight by clock on license master.
    • License Types
      • Standard
      • Enterprise Trial
      • Sales Trial
      • DEV/TEST
      • Free
      • Industrial IOT
      • Forwarder
  • Apps and Addons
    • Apps
      • Visualization
      • Analysis
      • Reports and Dashboard
      • User Interface
    • Add-Ons
      • Data Enrichment
      • Tags
      • Data Models
      • Datasets
    • Apps is a set of configuration files.
    • Addons are subset of apps. This will have a UI.
    • App can be from Splunk or Certified by Splunk by third parties. Apps can be free or premium.
• Configuration Files
  • Text documents that end in .conf extension and stored in /etc. System for global config files and app for application conf file. Splunk determines which conf files to use based on the app. Default directory /etc/app/default contains preconfigured conf files. Do not modify the conf files here. Place the modified conf files in /etc/<app>/local directory.
  • Conf files have [Stanza] and attribute key value pairs.

Below is the reference I used –

https://stackoverflow.com/questions/367706/how-do-i-parse-command-line-arguments-in-java

I ended up using commons cli library since it was lightweight and my use was very basic.

I used the below code provided in the stackoverflow as sample for my parsing use case.

or instance, this is how you use commons-cli to parse 2 string arguments:

import org.apache.commons.cli.*;

public class Main {


    public static void main(String[] args) throws Exception {

        Options options = new Options();

        Option input = new Option("i", "input", true, "input file path");
        input.setRequired(true);
        options.addOption(input);

        Option output = new Option("o", "output", true, "output file");
        output.setRequired(true);
        options.addOption(output);

        CommandLineParser parser = new DefaultParser();
        HelpFormatter formatter = new HelpFormatter();
        CommandLine cmd = null;//not a good practice, it serves it purpose 

        try {
            cmd = parser.parse(options, args);
        } catch (ParseException e) {
            System.out.println(e.getMessage());
            formatter.printHelp("utility-name", options);

            System.exit(1);
        }

        String inputFilePath = cmd.getOptionValue("input");
        String outputFilePath = cmd.getOptionValue("output");

        System.out.println(inputFilePath);
        System.out.println(outputFilePath);

    }

}

Below is the query used to check for the same –

SELECT s.sid, s.serial#, s.username, s.program, s.machine
FROM gv$session s
WHERE EXISTS (
  SELECT 1
  FROM gv$open_cursor c
  WHERE c.sid = s.sid
    AND c.status = 'OPEN'
    AND c.sql_text LIKE '%YOUR_TABLE_NAME%'
);