Welcome to Jeremy's page of technical wonders!

SELECT * FROM knowledge WHERE LOWER(content) LIKE '%cool%';

flowchart TB
    subgraph Clients [AWS CLIENTS - EKS EC2 ECS]
        FB_Agents[Fluent Bit Agents]
    end

    subgraph Streaming [1. INTERMEDIATE BUFFER - Async Handover]
        Kafka[Apache Kafka or AWS Kinesis]
    end

    subgraph Processing [2. INDEXING WORKERS - Aggregation and Transform]
        Processors[Indexing Service - Fluent Bit Aggregator Custom App ClickHouse Kafka Engine]
    end

    subgraph Datastore [3. DISTRIBUTED DATASTORE - Indexing and Storage]
        direction TB

        ClickHouseZoo[ClickHouse Keeper or ZooKeeper Cluster]

        subgraph Cluster [ClickHouse MergeTree Cluster - Scale Out]
            subgraph Shard1 [Shard 1]
                Replica1a[ClickHouse Replica A]
                Replica1b[ClickHouse Replica B]
            end

            subgraph Shard2 [Shard 2]
                Replica2a[ClickHouse Replica A]
                Replica2b[ClickHouse Replica B]
            end

            subgraph ShardN [Shard N]
                ReplicaNa[ClickHouse Replica A]
                ReplicaNb[ClickHouse Replica B]
            end
        end
    end

    FB_Agents -->|Write| Kafka
    Kafka -->|Consume| Processors
    Processors -->|Insert Batch| Cluster

    ClickHouseZoo <-->|Coordination| Cluster

    classDef orange fill:#f96,stroke:#333,stroke-width:2px
    classDef blue fill:#D1E8FF,stroke:#007bff,stroke-dasharray:5 5
    classDef gray fill:#ccc,stroke:#666

    class Kafka orange
    class Processors orange

import os

class KnowledgeBase:
    def __init__(self, file_path):
        self.file_path = file_path

    def select_like(self, pattern):
        pattern = pattern.lower()
        if not os.path.exists(self.file_path):
            return
            
        with open(self.file_path, 'r', encoding='utf-8') as f:
            for line in f:
                if pattern in line.lower():
                    yield line.strip()

# Usage
kb = KnowledgeBase('knowledge.txt')
results = kb.select_like('cool')

for row in results:
    print(row)