Implement indexing into Apache Druid #1
179
db.py
179
db.py
|
|
@ -1,15 +1,15 @@
|
|||
import random
|
||||
from math import ceil
|
||||
|
||||
import aioredis
|
||||
import manticoresearch
|
||||
import ujson
|
||||
from aiokafka import AIOKafkaProducer
|
||||
from manticoresearch.rest import ApiException
|
||||
from numpy import array_split
|
||||
from redis import StrictRedis
|
||||
|
||||
import util
|
||||
import random
|
||||
from aiokafka import AIOKafkaProducer
|
||||
|
||||
# Manticore schema
|
||||
from schemas import mc_s
|
||||
|
|
@ -21,6 +21,7 @@ api_instance = manticoresearch.IndexApi(api_client)
|
|||
|
||||
# Kafka
|
||||
from aiokafka import AIOKafkaProducer
|
||||
|
||||
KAFKA_TOPIC = "msg"
|
||||
|
||||
log = util.get_logger("db")
|
||||
|
|
@ -51,7 +52,7 @@ KEYPREFIX = "queue."
|
|||
|
||||
async def store_kafka_batch(data):
|
||||
print("STORING KAFKA BATCH")
|
||||
producer = AIOKafkaProducer(bootstrap_servers='kafka:9092')
|
||||
producer = AIOKafkaProducer(bootstrap_servers="kafka:9092")
|
||||
await producer.start()
|
||||
batch = producer.create_batch()
|
||||
for msg in data:
|
||||
|
|
@ -70,67 +71,74 @@ async def store_kafka_batch(data):
|
|||
del msg[key]
|
||||
if key in schema:
|
||||
if isinstance(value, int):
|
||||
if schema[key].startswith("string") or schema[key].startswith("text"):
|
||||
if schema[key].startswith("string") or schema[key].startswith(
|
||||
"text"
|
||||
):
|
||||
msg[key] = str(value)
|
||||
message = ujson.dumps(msg)
|
||||
body = str.encode(message)
|
||||
if "ts" not in msg:
|
||||
# print("MSG WITHOUT TS", msg)
|
||||
continue
|
||||
metadata = batch.append(key=None, value=body, timestamp=msg["ts"])
|
||||
if metadata is None:
|
||||
partitions = await producer.partitions_for(KAFKA_TOPIC)
|
||||
partition = random.choice(tuple(partitions))
|
||||
await producer.send_batch(batch, KAFKA_TOPIC, partition=partition)
|
||||
print("%d messages sent to partition %d"
|
||||
% (batch.record_count(), partition))
|
||||
print(
|
||||
"%d messages sent to partition %d" % (batch.record_count(), partition)
|
||||
)
|
||||
batch = producer.create_batch()
|
||||
continue
|
||||
|
||||
partitions = await producer.partitions_for(KAFKA_TOPIC)
|
||||
partition = random.choice(tuple(partitions))
|
||||
await producer.send_batch(batch, KAFKA_TOPIC, partition=partition)
|
||||
print("%d messages sent to partition %d"
|
||||
% (batch.record_count(), partition))
|
||||
print("%d messages sent to partition %d" % (batch.record_count(), partition))
|
||||
await producer.stop()
|
||||
|
||||
|
||||
# def store_message(msg):
|
||||
# """
|
||||
# Store a message into Manticore
|
||||
# :param msg: dict
|
||||
# """
|
||||
# store_kafka(msg)
|
||||
# # Duplicated to avoid extra function call
|
||||
# if msg["type"] in TYPES_MAIN:
|
||||
# index = "main"
|
||||
# schema = mc_s.schema_main
|
||||
# elif msg["type"] in TYPES_META:
|
||||
# index = "meta"
|
||||
# schema = mc_s.schema_meta
|
||||
# elif msg["type"] in TYPES_INT:
|
||||
# index = "internal"
|
||||
# schema = mc_s.schema_int
|
||||
# # normalise fields
|
||||
# for key, value in list(msg.items()):
|
||||
# if value is None:
|
||||
# del msg[key]
|
||||
# if key in schema:
|
||||
# if isinstance(value, int):
|
||||
# if schema[key].startswith("string") or schema[key].startswith("text"):
|
||||
# msg[key] = str(value)
|
||||
# # Duplicated to avoid extra function call
|
||||
# if msg["type"] in TYPES_MAIN:
|
||||
# index = "main"
|
||||
# schema = mc_s.schema_main
|
||||
# elif msg["type"] in TYPES_META:
|
||||
# index = "meta"
|
||||
# schema = mc_s.schema_meta
|
||||
# elif msg["type"] in TYPES_INT:
|
||||
# index = "internal"
|
||||
# schema = mc_s.schema_int
|
||||
# # normalise fields
|
||||
# for key, value in list(msg.items()):
|
||||
# if value is None:
|
||||
# del msg[key]
|
||||
# if key in schema:
|
||||
# if isinstance(value, int):
|
||||
# if schema[key].startswith("string") or schema[key].startswith("text"):
|
||||
# msg[key] = str(value)
|
||||
|
||||
# body = [{"insert": {"index": index, "doc": msg}}]
|
||||
# body_post = ""
|
||||
# for item in body:
|
||||
# body_post += ujson.dumps(item)
|
||||
# body_post += "\n"
|
||||
# body = [{"insert": {"index": index, "doc": msg}}]
|
||||
# body_post = ""
|
||||
# for item in body:
|
||||
# body_post += ujson.dumps(item)
|
||||
# body_post += "\n"
|
||||
|
||||
# # print(body_post)
|
||||
# try:
|
||||
# # Bulk index operations
|
||||
# print("FAKE POST")
|
||||
# #api_response = api_instance.bulk(body_post) # , async_req=True
|
||||
# # print(api_response)
|
||||
# except ApiException as e:
|
||||
# print("Exception when calling IndexApi->bulk: %s\n" % e)
|
||||
# print("ATTEMPT", body_post)
|
||||
|
||||
# # print(body_post)
|
||||
# try:
|
||||
# # Bulk index operations
|
||||
# print("FAKE POST")
|
||||
# #api_response = api_instance.bulk(body_post) # , async_req=True
|
||||
# # print(api_response)
|
||||
# except ApiException as e:
|
||||
# print("Exception when calling IndexApi->bulk: %s\n" % e)
|
||||
# print("ATTEMPT", body_post)
|
||||
|
||||
async def queue_message(msg):
|
||||
"""
|
||||
|
|
@ -139,9 +147,10 @@ async def queue_message(msg):
|
|||
src = msg["src"]
|
||||
message = ujson.dumps(msg)
|
||||
|
||||
key = "{KEYPREFIX}{src}"
|
||||
key = f"{KEYPREFIX}{src}"
|
||||
await ar.sadd(key, message)
|
||||
|
||||
|
||||
async def queue_message_bulk(data):
|
||||
"""
|
||||
Queue multiple messages on the Redis buffer.
|
||||
|
|
@ -150,7 +159,7 @@ async def queue_message_bulk(data):
|
|||
src = msg["src"]
|
||||
message = ujson.dumps(msg)
|
||||
|
||||
key = "{KEYPREFIX}{src}"
|
||||
key = f"{KEYPREFIX}{src}"
|
||||
await ar.sadd(key, message)
|
||||
|
||||
|
||||
|
|
@ -176,50 +185,50 @@ def queue_message_bulk_sync(data):
|
|||
# return
|
||||
# for msg in data:
|
||||
# store_kafka(msg)
|
||||
# # 10000: maximum inserts we can submit to
|
||||
# # Manticore as of Sept 2022
|
||||
# split_posts = array_split(data, ceil(len(data) / 10000))
|
||||
# for messages in split_posts:
|
||||
# total = []
|
||||
# for msg in messages:
|
||||
# # Duplicated to avoid extra function call (see above)
|
||||
# if msg["type"] in TYPES_MAIN:
|
||||
# index = "main"
|
||||
# schema = mc_s.schema_main
|
||||
# elif msg["type"] in TYPES_META:
|
||||
# index = "meta"
|
||||
# schema = mc_s.schema_meta
|
||||
# elif msg["type"] in TYPES_INT:
|
||||
# index = "internal"
|
||||
# schema = mc_s.schema_int
|
||||
# # normalise fields
|
||||
# for key, value in list(msg.items()):
|
||||
# if value is None:
|
||||
# del msg[key]
|
||||
# if key in schema:
|
||||
# if isinstance(value, int):
|
||||
# if schema[key].startswith("string") or schema[key].startswith(
|
||||
# "text"
|
||||
# ):
|
||||
# msg[key] = str(value)
|
||||
# # 10000: maximum inserts we can submit to
|
||||
# # Manticore as of Sept 2022
|
||||
# split_posts = array_split(data, ceil(len(data) / 10000))
|
||||
# for messages in split_posts:
|
||||
# total = []
|
||||
# for msg in messages:
|
||||
# # Duplicated to avoid extra function call (see above)
|
||||
# if msg["type"] in TYPES_MAIN:
|
||||
# index = "main"
|
||||
# schema = mc_s.schema_main
|
||||
# elif msg["type"] in TYPES_META:
|
||||
# index = "meta"
|
||||
# schema = mc_s.schema_meta
|
||||
# elif msg["type"] in TYPES_INT:
|
||||
# index = "internal"
|
||||
# schema = mc_s.schema_int
|
||||
# # normalise fields
|
||||
# for key, value in list(msg.items()):
|
||||
# if value is None:
|
||||
# del msg[key]
|
||||
# if key in schema:
|
||||
# if isinstance(value, int):
|
||||
# if schema[key].startswith("string") or schema[key].startswith(
|
||||
# "text"
|
||||
# ):
|
||||
# msg[key] = str(value)
|
||||
|
||||
# body = {"insert": {"index": index, "doc": msg}}
|
||||
# total.append(body)
|
||||
# body = {"insert": {"index": index, "doc": msg}}
|
||||
# total.append(body)
|
||||
|
||||
# body_post = ""
|
||||
# for item in total:
|
||||
# body_post += ujson.dumps(item)
|
||||
# body_post += "\n"
|
||||
# body_post = ""
|
||||
# for item in total:
|
||||
# body_post += ujson.dumps(item)
|
||||
# body_post += "\n"
|
||||
|
||||
# # print(body_post)
|
||||
# try:
|
||||
# # Bulk index operations
|
||||
# print("FAKE POST")
|
||||
# #api_response = api_instance.bulk(body_post) # , async_req=True
|
||||
# #print(api_response)
|
||||
# except ApiException as e:
|
||||
# print("Exception when calling IndexApi->bulk: %s\n" % e)
|
||||
# print("ATTEMPT", body_post)
|
||||
# # print(body_post)
|
||||
# try:
|
||||
# # Bulk index operations
|
||||
# print("FAKE POST")
|
||||
# #api_response = api_instance.bulk(body_post) # , async_req=True
|
||||
# #print(api_response)
|
||||
# except ApiException as e:
|
||||
# print("Exception when calling IndexApi->bulk: %s\n" % e)
|
||||
# print("ATTEMPT", body_post)
|
||||
|
||||
|
||||
# def update_schema():
|
||||
|
|
@ -243,5 +252,5 @@ def queue_message_bulk_sync(data):
|
|||
# util_instance.sql(create_query)
|
||||
|
||||
|
||||
#create_index(api_client)
|
||||
#update_schema()
|
||||
# create_index(api_client)
|
||||
# update_schema()
|
||||
|
|
|
|||
|
|
@ -19,7 +19,11 @@ services:
|
|||
- .env
|
||||
volumes_from:
|
||||
- tmp
|
||||
# depends_on:
|
||||
depends_on:
|
||||
- broker
|
||||
- kafka
|
||||
- tmp
|
||||
- redis
|
||||
# - db
|
||||
|
||||
threshold:
|
||||
|
|
@ -52,12 +56,16 @@ services:
|
|||
- 9093:9090
|
||||
environment:
|
||||
- DRUID_BROKER_URL=http://broker:8082
|
||||
depends_on:
|
||||
- broker
|
||||
|
||||
metabase:
|
||||
container_name: metabase
|
||||
image: metabase/metabase:latest
|
||||
ports:
|
||||
- 3001:3000
|
||||
depends_on:
|
||||
- broker
|
||||
|
||||
postgres:
|
||||
container_name: postgres
|
||||
|
|
@ -82,6 +90,7 @@ services:
|
|||
image: bitnami/kafka
|
||||
depends_on:
|
||||
- zookeeper
|
||||
- broker
|
||||
ports:
|
||||
- 29092:29092
|
||||
- 9092:9092
|
||||
|
|
|
|||
|
|
@ -1,11 +1,11 @@
|
|||
import asyncio
|
||||
from os import getenv
|
||||
|
||||
import db
|
||||
import util
|
||||
from sources.ch4 import Chan4
|
||||
from sources.dis import DiscordClient
|
||||
from sources.ingest import Ingest
|
||||
import db
|
||||
|
||||
# For development
|
||||
# if not getenv("DISCORD_TOKEN", None):
|
||||
|
|
@ -27,7 +27,6 @@ async def main(loop):
|
|||
log.info("Starting Discord handler.")
|
||||
client = DiscordClient()
|
||||
loop.create_task(client.start(token))
|
||||
# client.run(token)
|
||||
|
||||
log.info("Starting 4chan handler.")
|
||||
chan = Chan4()
|
||||
|
|
|
|||
|
|
@ -1,7 +1,20 @@
|
|||
from concurrent.futures import ProcessPoolExecutor
|
||||
import asyncio
|
||||
import os
|
||||
import random
|
||||
|
||||
# For key generation
|
||||
import string
|
||||
from concurrent.futures import ProcessPoolExecutor
|
||||
|
||||
# For timestamp processing
|
||||
from datetime import datetime
|
||||
from math import ceil
|
||||
|
||||
import ujson
|
||||
|
||||
# For 4chan message parsing
|
||||
from bs4 import BeautifulSoup
|
||||
from numpy import array_split
|
||||
from siphashc import siphash
|
||||
|
||||
import db
|
||||
|
|
@ -10,19 +23,6 @@ import util
|
|||
# 4chan schema
|
||||
from schemas.ch4_s import ATTRMAP
|
||||
|
||||
# For key generation
|
||||
import string
|
||||
import random
|
||||
|
||||
# For timestamp processing
|
||||
import datetime
|
||||
|
||||
# For 4chan message parsing
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
from numpy import array_split
|
||||
from math import ceil
|
||||
|
||||
log = util.get_logger("process")
|
||||
|
||||
# Maximum number of CPU threads to use for post processing
|
||||
|
|
@ -30,6 +30,7 @@ CPU_THREADS = os.cpu_count()
|
|||
|
||||
p = ProcessPoolExecutor(CPU_THREADS)
|
||||
|
||||
|
||||
def get_hash_key():
|
||||
hash_key = db.r.get("hashing_key")
|
||||
if not hash_key:
|
||||
|
|
@ -42,33 +43,68 @@ def get_hash_key():
|
|||
log.debug(f"Decoded hash key: {hash_key}")
|
||||
return hash_key
|
||||
|
||||
|
||||
hash_key = get_hash_key()
|
||||
|
||||
|
||||
@asyncio.coroutine
|
||||
async def spawn_processing_threads(data):
|
||||
print("SPAWN", data)
|
||||
loop = asyncio.get_event_loop()
|
||||
tasks = []
|
||||
oldts = [x["now"] for x in data if "now" in x]
|
||||
if len(data) < CPU_THREADS:
|
||||
split_data = [data]
|
||||
else:
|
||||
msg_per_core = int(len(data) / CPU_THREADS)
|
||||
print("MSG PER CORE", msg_per_core)
|
||||
split_data = array_split(data, ceil(len(data) / msg_per_core))
|
||||
print("SPLIT DATA", split_data)
|
||||
for split in split_data:
|
||||
for index, split in enumerate(split_data):
|
||||
print("DELEGATING TO THREAD", len(split))
|
||||
await process_data_thread(split)
|
||||
future = loop.run_in_executor(p, process_data, data)
|
||||
# future = p.submit(process_data, split)
|
||||
tasks.append(future)
|
||||
# results = [x.result(timeout=50) for x in tasks]
|
||||
results = await asyncio.gather(*tasks)
|
||||
print("RESULTS", len(results))
|
||||
|
||||
# Join the results back from the split list
|
||||
flat_list = [item for sublist in results for item in sublist]
|
||||
print("LENFLAT", len(flat_list))
|
||||
print("LENDATA", len(data))
|
||||
|
||||
newts = [x["ts"] for x in flat_list if "ts" in x]
|
||||
print("lenoldts", len(oldts))
|
||||
print("lennewts", len(newts))
|
||||
allts = all(["ts" in x for x in flat_list])
|
||||
print("ALLTS", allts)
|
||||
alllen = [len(x) for x in flat_list]
|
||||
print("ALLLEN", alllen)
|
||||
await db.store_kafka_batch(flat_list)
|
||||
|
||||
|
||||
# @asyncio.coroutine
|
||||
# def process_data_thread(data):
|
||||
# """
|
||||
# Helper to spawn threads to process a list of data.
|
||||
# """
|
||||
# loop = asyncio.get_event_loop()
|
||||
# if len(data) < CPU_THREADS:
|
||||
# split_data = [data]
|
||||
# else:
|
||||
# msg_per_core = int(len(data) / CPU_THREADS)
|
||||
# print("MSG PER CORE", msg_per_core)
|
||||
# split_data = array_split(data, ceil(len(data) / msg_per_core))
|
||||
# for index, split in enumerate(split_data):
|
||||
# print("DELEGATING TO THREAD", len(split))
|
||||
# #f = process_data_thread(split)
|
||||
# yield loop.run_in_executor(p, process_data, data)
|
||||
|
||||
@asyncio.coroutine
|
||||
def process_data_thread(data):
|
||||
"""
|
||||
Helper to spawn threads to process a list of data.
|
||||
"""
|
||||
loop = asyncio.get_event_loop()
|
||||
yield from loop.run_in_executor(p, process_data, data)
|
||||
|
||||
def process_data(data):
|
||||
print("PROCESSING DATA", data)
|
||||
print("PROCESS DATA START")
|
||||
# to_store = []
|
||||
for index, msg in enumerate(data):
|
||||
#print("PROCESSING", msg)
|
||||
# print("PROCESSING", msg)
|
||||
if msg["src"] == "4ch":
|
||||
board = msg["net"]
|
||||
thread = msg["channel"]
|
||||
|
|
@ -81,15 +117,18 @@ def process_data(data):
|
|||
if key_content:
|
||||
key_content = key_content.decode("ascii")
|
||||
if key_content == hash:
|
||||
del data[index]
|
||||
continue
|
||||
else:
|
||||
data[index][index]["type"] = "update"
|
||||
data[index]["type"] = "update"
|
||||
db.r.set(redis_key, hash)
|
||||
for key2, value in list(msg.items()):
|
||||
if "now" not in data[index]:
|
||||
print("NOW NOT IN INDEX", data[index])
|
||||
for key2, value in list(data[index].items()):
|
||||
if key2 in ATTRMAP:
|
||||
msg[ATTRMAP[key2]] = data[index][key2]
|
||||
data[index][ATTRMAP[key2]] = data[index][key2]
|
||||
del data[index][key2]
|
||||
if "ts" in msg:
|
||||
if "ts" in data[index]:
|
||||
old_time = data[index]["ts"]
|
||||
# '08/30/22(Tue)02:25:37'
|
||||
time_spl = old_time.split(":")
|
||||
|
|
@ -100,7 +139,13 @@ def process_data(data):
|
|||
# new_ts = old_ts.isoformat()
|
||||
new_ts = int(old_ts.timestamp())
|
||||
data[index]["ts"] = new_ts
|
||||
else:
|
||||
print("MSG WITHOUT TS PROCESS", data[index])
|
||||
continue
|
||||
if "msg" in msg:
|
||||
soup = BeautifulSoup(data[index]["msg"], "html.parser")
|
||||
msg = soup.get_text(separator="\n")
|
||||
data[index]["msg"] = msg
|
||||
data[index]["msg"] = msg
|
||||
# to_store.append(data[index])
|
||||
print("FINISHED PROCESSING DATA")
|
||||
return data
|
||||
|
|
|
|||
|
|
@ -136,7 +136,7 @@ class Chan4(object):
|
|||
# Split into 10,000 chunks
|
||||
if not all_posts:
|
||||
return
|
||||
self.handle_posts(all_posts)
|
||||
await self.handle_posts(all_posts)
|
||||
# threads_per_core = int(len(all_posts) / CPU_THREADS)
|
||||
# for i in range(CPU_THREADS):
|
||||
# new_dict = {}
|
||||
|
|
@ -146,8 +146,7 @@ class Chan4(object):
|
|||
# new_dict[k].append(v)
|
||||
# else:
|
||||
# new_dict[k] = [v]
|
||||
#await self.handle_posts_thread(new_dict)
|
||||
|
||||
# await self.handle_posts_thread(new_dict)
|
||||
|
||||
# print("VAL", ceil(len(all_posts) / threads_per_core))
|
||||
# split_posts = array_split(all_posts, ceil(len(all_posts) / threads_per_core))
|
||||
|
|
|
|||
|
|
@ -4,24 +4,22 @@ import ujson
|
|||
|
||||
import db
|
||||
import util
|
||||
|
||||
from processing import process
|
||||
|
||||
SOURCES = ["irc", "dis", "4ch"]
|
||||
SOURCES = ["4ch", "irc", "dis"]
|
||||
KEYPREFIX = "queue."
|
||||
CHUNK_SIZE = 1000
|
||||
CHUNK_SIZE = 90000
|
||||
ITER_DELAY = 0.5
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
class Ingest(object):
|
||||
def __init__(self):
|
||||
name = self.__class__.__name__
|
||||
self.log = util.get_logger(name)
|
||||
|
||||
async def run(self):
|
||||
# items = [{'no': 23567753, 'now': '09/12/22(Mon)20:10:29', 'name': 'Anonysmous', 'filename': '1644986767568', 'ext': '.webm', 'w': 1280, 'h': 720, 'tn_w': 125, 'tn_h': 70, 'tim': 1663027829301457, 'time': 1663027829, 'md5': 'zeElr1VR05XpZ2XuAPhmPA==', 'fsize': 3843621, 'resto': 23554700, 'type': 'msg', 'src': '4ch', 'net': 'gif', 'channel': '23554700'}]
|
||||
# await process.spawn_processing_threads(items)
|
||||
while True:
|
||||
await self.get_chunk()
|
||||
await asyncio.sleep(ITER_DELAY)
|
||||
|
|
@ -33,13 +31,11 @@ class Ingest(object):
|
|||
chunk = await db.ar.spop(key, CHUNK_SIZE)
|
||||
if not chunk:
|
||||
continue
|
||||
#self.log.info(f"Got chunk: {chunk}")
|
||||
# self.log.info(f"Got chunk: {chunk}")
|
||||
for item in chunk:
|
||||
item = ujson.loads(item)
|
||||
#self.log.info(f"Got item: {item}")
|
||||
# self.log.info(f"Got item: {item}")
|
||||
items.append(item)
|
||||
if items:
|
||||
print("PROCESSING", len(items))
|
||||
await process.spawn_processing_threads(items)
|
||||
print("DONE WITH PROCESSING", len(items))
|
||||
await db.store_kafka_batch(items)
|
||||
|
|
|
|||
Loading…
Reference in New Issue