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https://github.com/20kaushik02/real-time-traffic-analysis-clickhouse.git
synced 2025-12-06 08:04:06 +00:00
added option for streaming from csv
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@ -50,10 +50,13 @@ services:
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aliases:
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- pcap_streamer
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volumes:
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- "/host_mnt/c/Users/akash/storage/Asu/sem3/dds/project:/data/pcap"
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# - "/host_mnt/c/Users/akash/storage/Asu/sem3/dds/project:/data/pcap"
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- "./:/data/pcap"
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- "./:/data/csv"
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environment:
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PCAP_FILE: /data/pcap/202310081400.pcap
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command: ["sh", "-c", "sleep 30 && python /app/pcap_processor.py -f /data/pcap/202310081400.pcap -s --stream_size 1000"]
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# command: ["sh", "-c", "sleep 30 && python /app/pcap_processor.py -f /data/pcap/202310081400.pcap -s --stream_size 1000"]
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command: ["sh", "-c", "sleep 30 && python /app/pcap_processor.py -c /data/csv/sample_output.csv -s --stream_size 1000"]
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deploy:
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replicas: 1
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restart_policy:
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@ -113,6 +113,21 @@ def create_pkt_object(pkt: Packet) -> dict:
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return res_json
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def row_to_dict(pkt_row: list) -> dict:
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"""make dict from CSV row"""
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return {
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"time": float(pkt_row[0]),
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"l4_proto": pkt_row[1],
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"src_addr": pkt_row[2],
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"dst_addr": pkt_row[3],
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"src_port": int(pkt_row[4]),
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"dst_port": int(pkt_row[5]),
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"pkt_len": int(pkt_row[6]),
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}
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def prep_csv(out_file: str):
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with open(out_file, "w", newline="") as csvfile:
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writer = csv.writer(csvfile)
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@ -139,7 +154,8 @@ def pkts_write_csv(pkts: list, out_file: str):
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if __name__ == "__main__":
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argp = ArgumentParser()
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argp.add_argument("-f", "--pcap_file", required=True, dest="_pcap")
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argp.add_argument("-f", "--pcap_file", required=False, dest="_pcap")
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argp.add_argument("-c", "--csv_file", required=False, dest="_csv")
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argp.add_argument("-o", "--out_file", required=False, dest="_out")
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argp.add_argument("--stream_size", required=False, default=10000, dest="_streamsize")
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argp.add_argument(
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@ -169,6 +185,7 @@ if __name__ == "__main__":
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args = argp.parse_args()
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pcap_file = args._pcap
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csv_file = args._csv
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out_file = args._out
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streaming = args._stream
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sample = args._sample
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@ -179,41 +196,59 @@ if __name__ == "__main__":
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sample_size = samplesize #1000000
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batch_size = 100 #100000
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pcap_rdr = PcapReader(pcap_file)
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if not streaming:
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assert args._out and args._out != ""
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prep_csv(out_file)
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# if preprocessed data ready for streaming
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if csv_file:
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with open(csv_file, newline="") as f:
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csv_rdr = csv.reader(f)
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next(csv_rdr) # skip headers
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pkts = []
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pkts = []
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cnt = 0
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seen_count = 0
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for idx, pkt in enumerate(pcap_rdr):
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seen_count += 1
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# filter packets
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if not pkt_filter(pkt):
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continue
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for idx, row in enumerate(csv_rdr):
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# direct streaming to kafka goes here
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producer.client.send(KAFKA_TOPIC, row_to_dict(row))
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dbg_print(row_to_dict(row))
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dbg_print("streamed packet", idx)
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if idx > sample_size:
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break
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dbg_print(f"total streamed: {idx}")
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# otherwise, process packets
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else:
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pcap_rdr = PcapReader(pcap_file)
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if not streaming:
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# write to file
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pkts.append(pkt_extract(pkt))
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assert args._out and args._out != ""
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prep_csv(out_file)
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if sample and idx > sample_size:
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break
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pkts = []
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cnt = 0
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seen_count = 0
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for idx, pkt in enumerate(pcap_rdr):
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seen_count += 1
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# filter packets
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if not pkt_filter(pkt):
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continue
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if idx > 0 and idx % batch_size == 0:
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pkts_write_csv(pkts, out_file)
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pkts = []
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else:
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# direct streaming to kafka goes here
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packet_data = create_pkt_object(pkt)
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producer.client.send(KAFKA_TOPIC, packet_data)
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cnt += 1
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#print(f"streamed packet at index {idx} ")
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if idx > sample_size: break
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print(f"total seen: {seen_count-1}")
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print(f"total streamed: {cnt}")
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# flush remaining
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if not streaming and len(pkts) > 0:
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pkts_write_csv(pkts, out_file)
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if not streaming:
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# write to file
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pkts.append(pkt_extract(pkt))
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if sample and idx > sample_size:
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break
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if idx > 0 and idx % batch_size == 0:
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pkts_write_csv(pkts, out_file)
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pkts = []
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else:
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# direct streaming to kafka goes here
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packet_data = create_pkt_object(pkt)
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producer.client.send(KAFKA_TOPIC, packet_data)
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cnt += 1
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# print(f"streamed packet at index {idx} ")
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if idx > sample_size:
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break
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print(f"total seen: {seen_count-1}")
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print(f"total streamed: {cnt}")
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# flush remaining
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if not streaming and len(pkts) > 0:
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pkts_write_csv(pkts, out_file)
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