mehrabi
4 months ago
commit
193b0f72bd
2 changed files with 541 additions and 0 deletions
-
368load_postgres.py
-
173load_redis.py
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import csv |
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import os |
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import psycopg2 |
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from psycopg2 import sql |
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import multiprocessing as mp |
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from concurrent.futures import ProcessPoolExecutor, as_completed |
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import time |
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import sys |
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import random |
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import tempfile |
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# ═══════════════════════════════════════════════════════════════ |
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# تنظیمات |
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# ═══════════════════════════════════════════════════════════════ |
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DB_CONFIG = { |
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"host": "localhost", |
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"port": 5432, |
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"database": "numbers_db", |
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"user": "myuser", |
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"password": "mypassword" |
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} |
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CSV_FILE = "numbers.csv" |
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TABLE_NAME = "phone_numbers" |
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COLUMN_NAME = "phone_number" |
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RANDOM_COLUMN_NAME = "random_code" |
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NUM_WORKERS = 12 |
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BATCH_SIZE = 2_000_000 |
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# ═══════════════════════════════════════════════════════════════ |
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# شروع توالی عددی |
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# ═══════════════════════════════════════════════════════════════ |
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PHONE_START = 100_000_000 # کمترین عدد ۹ رقمی |
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def optimize_connection(conn): |
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"""تنظیمات بهینه برای سرعت حداکثری""" |
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with conn.cursor() as cur: |
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cur.execute("SET work_mem = '512MB'") |
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cur.execute("SET synchronous_commit = OFF") |
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cur.execute("SET maintenance_work_mem = '2GB'") |
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cur.execute("SET max_parallel_workers_per_gather = 4") |
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cur.execute("SET random_page_cost = 1.1") |
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conn.commit() |
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def get_file_chunks(filename, num_chunks): |
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"""تقسیم فایل به بخشهای مساوی""" |
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print(f"Calculating chunks for {filename}...") |
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file_size = os.path.getsize(filename) |
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print(f"File size: {file_size / (1024 ** 3):.2f} GB") |
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chunk_size = file_size // num_chunks |
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chunks = [] |
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with open(filename, 'rb') as f: |
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f.readline() |
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start = f.tell() |
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for i in range(num_chunks): |
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if i < num_chunks - 1: |
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f.seek(chunk_size * (i + 1)) |
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f.readline() |
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end = f.tell() |
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chunks.append((start, end)) |
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start = end |
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else: |
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chunks.append((start, file_size)) |
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print(f"Created {len(chunks)} chunks") |
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return chunks |
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def count_total_rows(): |
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"""شمارش کل رکوردها""" |
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print("Counting total rows...") |
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count = 0 |
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with open(CSV_FILE, 'r') as f: |
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next(f) |
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for _ in f: |
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count += 1 |
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return count |
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def load_chunk(args): |
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"""هر Worker یک فایل temp میسازد و با COPY لود میکند""" |
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chunk_start, chunk_end, worker_id, rows_in_chunk = args |
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print(f"[Worker {worker_id}] Starting... chunk: {chunk_start} to {chunk_end}") |
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conn = psycopg2.connect(**DB_CONFIG) |
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temp_file = None |
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try: |
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optimize_connection(conn) |
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print(f"[Worker {worker_id}] Connected to DB") |
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start_time = time.time() |
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loaded = 0 |
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# ═══════════════════════════════════════════════════════ |
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# محاسبه شروع عدد توالی برای این Worker |
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# ═══════════════════════════════════════════════════════ |
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phone_start = PHONE_START + (worker_id * rows_in_chunk) |
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current_phone = phone_start |
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print(f"[Worker {worker_id}] Phone range: {phone_start:,} to {phone_start + rows_in_chunk - 1:,}") |
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temp_fd, temp_file = tempfile.mkstemp(suffix='.csv', prefix=f'worker_{worker_id}_') |
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os.close(temp_fd) |
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with open(temp_file, 'w', buffering=8192 * 1024) as temp_f: |
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with open(CSV_FILE, 'r', buffering=8192 * 1024) as f: |
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f.seek(chunk_start) |
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# رد کردن خط header اگر در ابتدای chunk باشد |
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if chunk_start > 0: |
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f.readline() |
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while f.tell() < chunk_end: |
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line = f.readline() |
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if line.strip(): |
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# ═══════════════════════════════════════ |
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# استفاده از عدد توالی به جای خواندن از CSV |
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# ═══════════════════════════════════════ |
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random_code = random.randint(1000, 9999) |
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temp_f.write(f"{current_phone},{random_code}\n") |
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current_phone += 1 |
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loaded += 1 |
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if loaded % 5_000_000 == 0: |
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print(f"[Worker {worker_id}] Wrote {loaded:,} rows to temp file") |
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print(f"[Worker {worker_id}] Temp file created: {loaded:,} rows") |
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with open(temp_file, 'r') as f: |
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with conn.cursor() as cur: |
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cur.copy_expert( |
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f"COPY {TABLE_NAME} ({COLUMN_NAME}, {RANDOM_COLUMN_NAME}) FROM STDIN WITH CSV", |
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f |
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) |
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conn.commit() |
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elapsed = time.time() - start_time |
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rate = loaded / elapsed if elapsed > 0 else 0 |
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print(f"[Worker {worker_id}] Done! {loaded:,} rows in {elapsed:.1f}s ({rate:,.0f} rows/sec)") |
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return loaded |
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except Exception as e: |
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print(f"[Worker {worker_id}] ERROR: {e}") |
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raise |
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finally: |
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conn.close() |
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if temp_file and os.path.exists(temp_file): |
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os.remove(temp_file) |
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def create_table(conn): |
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"""ساخت جدول Unlogged برای سرعت بیشتر""" |
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with conn.cursor() as cur: |
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cur.execute(f""" |
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DROP TABLE IF EXISTS {TABLE_NAME} CASCADE; |
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CREATE UNLOGGED TABLE {TABLE_NAME} ( |
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{COLUMN_NAME} BIGINT NOT NULL, |
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{RANDOM_COLUMN_NAME} INTEGER NOT NULL |
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) WITH (fillfactor = 100); |
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""") |
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conn.commit() |
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def index_exists(conn, index_name): |
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"""بررسی وجود ایندکس""" |
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with conn.cursor() as cur: |
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cur.execute(""" |
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SELECT EXISTS ( |
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SELECT 1 FROM pg_indexes |
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WHERE indexname = %s |
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) |
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""", (index_name,)) |
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return cur.fetchone()[0] |
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def create_index(conn, column_name): |
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"""ساخت ایندکس با بررسی و تأیید""" |
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index_name = f"idx_{TABLE_NAME}_{column_name}" |
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print(f"\n>>> Creating index on '{column_name}'...") |
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if index_exists(conn, index_name): |
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print(f" Index '{index_name}' already exists, dropping...") |
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with conn.cursor() as cur: |
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cur.execute(f"DROP INDEX IF EXISTS {index_name}") |
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conn.commit() |
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with conn.cursor() as cur: |
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start = time.time() |
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cur.execute(f"CREATE INDEX {index_name} ON {TABLE_NAME} ({column_name})") |
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conn.commit() |
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elapsed = time.time() - start |
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print(f" ✓ Index '{index_name}' created in {elapsed:.1f}s") |
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if index_exists(conn, index_name): |
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print(f" ✓ Verified: Index '{index_name}' exists") |
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return True |
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else: |
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print(f" ✗ ERROR: Index '{index_name}' was not created!") |
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return False |
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def verify_indexes(): |
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"""تأیید نهایی وجود همه ایندکسها""" |
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conn = psycopg2.connect(**DB_CONFIG) |
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try: |
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print("\n" + "=" * 50) |
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print("INDEX VERIFICATION") |
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print("=" * 50) |
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with conn.cursor() as cur: |
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cur.execute(""" |
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SELECT indexname, indexdef |
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FROM pg_indexes |
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WHERE tablename = %s |
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ORDER BY indexname |
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""", (TABLE_NAME,)) |
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indexes = cur.fetchall() |
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if not indexes: |
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print("✗ NO INDEXES FOUND!") |
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return False |
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print(f"\nFound {len(indexes)} index(es):\n") |
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for idx_name, idx_def in indexes: |
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print(f" ✓ {idx_name}") |
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print(f" Definition: {idx_def}\n") |
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phone_idx_exists = any('phone_number' in idx[1] for idx in indexes) |
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random_idx_exists = any('random_code' in idx[1] for idx in indexes) |
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print("-" * 50) |
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print(f"phone_number indexed: {'✓ YES' if phone_idx_exists else '✗ NO'}") |
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print(f"random_code indexed: {'✓ YES' if random_idx_exists else '✗ NO'}") |
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print("-" * 50) |
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return phone_idx_exists and random_idx_exists |
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finally: |
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conn.close() |
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def verify_data(start_check=100_000_000, sample_points=None): |
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"""بررسی صحت دادههای لود شده""" |
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if sample_points is None: |
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sample_points = [0, 10_000_000, 50_000_000, 100_000_000, 124_999_999] |
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print("\n" + "=" * 50) |
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print("DATA VERIFICATION") |
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print("=" * 50) |
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conn = psycopg2.connect(**DB_CONFIG) |
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try: |
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with conn.cursor() as cur: |
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for point in sample_points: |
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expected_phone = PHONE_START + point |
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cur.execute( |
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f"SELECT {COLUMN_NAME}, {RANDOM_COLUMN_NAME} FROM {TABLE_NAME} LIMIT 1 OFFSET %s", |
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(point,) |
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) |
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row = cur.fetchone() |
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if row: |
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status = "✓" if row[0] == expected_phone else "✗" |
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print(f" {status} Offset {point:>12,}: Expected {expected_phone:,}, Got {row[0]:,}") |
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finally: |
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conn.close() |
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def main(): |
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print("=" * 60) |
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print("PostgreSQL Bulk Loader - Sequential Phone Numbers") |
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print("=" * 60) |
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print(f"Phone number range: {PHONE_START:,} to {PHONE_START + 125_000_000 - 1:,}") |
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print(f"Total records: 125,000,000\n") |
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num_workers = min(NUM_WORKERS, mp.cpu_count()) |
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total_rows = count_total_rows() |
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print(f"CSV rows: {total_rows:,}") |
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print(f"Using {num_workers} workers") |
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print(f"Batch size: {BATCH_SIZE:,}\n") |
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start_time = time.time() |
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try: |
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# اتصال اولیه و ساخت جدول |
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conn = psycopg2.connect(**DB_CONFIG) |
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print("Connected to DB, creating UNLOGGED table...") |
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optimize_connection(conn) |
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create_table(conn) |
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conn.close() |
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print("Table ready\n") |
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# تقسیم فایل |
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print("Calculating file chunks...") |
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chunks = get_file_chunks(CSV_FILE, num_workers) |
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# ═══════════════════════════════════════════════════════ |
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# محاسبه تعداد رکوردها در هر chunk |
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# ═══════════════════════════════════════════════════════ |
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rows_per_chunk = total_rows // num_workers |
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args = [ |
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(start, end, i, rows_per_chunk) |
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for i, (start, end) in enumerate(chunks) |
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] |
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print("\nStarting workers...\n") |
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# اجرای موازی |
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with ProcessPoolExecutor(max_workers=num_workers) as executor: |
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futures = [executor.submit(load_chunk, arg) for arg in args] |
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total = 0 |
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for future in as_completed(futures): |
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try: |
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total += future.result() |
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except Exception as e: |
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print(f"Worker failed: {e}") |
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elapsed = time.time() - start_time |
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rate = total / elapsed if elapsed > 0 else 0 |
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remaining = (total_rows - total) / rate if rate > 0 else 0 |
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percent = (total * 100) // total_rows |
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print(f"\n>>> Progress: {total:,}/{total_rows:,} ({percent}%) | " |
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f"Speed: {rate:,.0f} rows/sec | " |
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f"ETA: {remaining / 60:.1f} min") |
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print(f"\n✓ Total rows loaded: {total:,}") |
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# ═══════════════════════════════════════════════════════ |
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# ساخت ایندکسها با تأیید |
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# ═══════════════════════════════════════════════════════ |
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print("\n" + "=" * 60) |
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print("CREATING INDEXES") |
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print("=" * 60) |
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conn = psycopg2.connect(**DB_CONFIG) |
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success1 = create_index(conn, COLUMN_NAME) |
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conn.close() |
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# ═══════════════════════════════════════════════════════ |
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# تأیید نهایی |
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# ═══════════════════════════════════════════════════════ |
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all_ok = verify_indexes() |
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# بررسی صحت دادهها |
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verify_data() |
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total_time = time.time() - start_time |
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print(f"\n✓ Done! Total time: {total_time / 60:.1f} minutes") |
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print(f"✓ Average speed: {total_rows / total_time:,.0f} rows/sec") |
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if all_ok: |
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print("\n✓✓✓ ALL INDEXES CREATED SUCCESSFULLY ✓✓✓") |
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else: |
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print("\n✗✗✗ SOME INDEXES MISSING! ✗✗✗") |
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except Exception as e: |
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print(f"\n✗ Error: {e}") |
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import traceback |
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traceback.print_exc() |
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if __name__ == "__main__": |
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main() |
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@ -0,0 +1,173 @@ |
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import os |
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import redis |
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import multiprocessing as mp |
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from concurrent.futures import ProcessPoolExecutor, as_completed |
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import time |
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import random |
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# ───────────────────────────────────────────── |
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# کانفیگ Redis |
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# ───────────────────────────────────────────── |
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REDIS_CONFIG = { |
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"host": "localhost", |
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"port": 6379, |
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"db": 0, |
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"decode_responses": True, |
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"socket_connect_timeout": 5, |
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"socket_keepalive": True, |
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} |
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NUM_WORKERS = 8 |
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BATCH_SIZE = 100_000 |
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# ═══════════════════════════════════════════════════════════════ |
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# بازه اعداد - مطابق با دادههای لود شده |
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# ═══════════════════════════════════════════════════════════════ |
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TOTAL_RECORDS = 125_000_000 |
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PHONE_START = 100_000_000 |
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PHONE_END = PHONE_START + TOTAL_RECORDS - 1 # 224,999,999 |
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def optimize_redis(r): |
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"""تنظیمات بهینه Redis""" |
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r.config_set("maxmemory", "16gb") |
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r.config_set("maxmemory-policy", "allkeys-lru") |
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r.config_set("save", "") |
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print("✓ Redis optimized") |
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def load_chunk_to_redis(args): |
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"""لود یک بخش از بازه اعداد به Redis""" |
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worker_id, start_phone, end_phone = args |
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r = redis.Redis(**REDIS_CONFIG) |
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try: |
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print(f"[Worker {worker_id}] Starting... phone: {start_phone:,} to {end_phone:,}") |
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loaded = 0 |
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batch_count = 0 |
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start_time = time.time() |
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pipe = r.pipeline() |
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current_phone = start_phone |
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while current_phone <= end_phone: |
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random_value = random.randint(1000, 9999) |
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pipe.set(str(current_phone), random_value) |
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loaded += 1 |
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current_phone += 1 |
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|
if loaded >= BATCH_SIZE * (batch_count + 1): |
||||
|
pipe.execute() |
||||
|
batch_count += 1 |
||||
|
elapsed = time.time() - start_time |
||||
|
rate = loaded / elapsed if elapsed > 0 else 0 |
||||
|
print(f"[Worker {worker_id}] Batch {batch_count} done ({loaded:,} rows, {rate:,.0f} rows/sec)") |
||||
|
|
||||
|
if len(pipe.command_stack) > 0: |
||||
|
pipe.execute() |
||||
|
|
||||
|
elapsed = time.time() - start_time |
||||
|
rate = loaded / elapsed if elapsed > 0 else 0 |
||||
|
print(f"[Worker {worker_id}] Done! {loaded:,} rows in {elapsed:.1f}s ({rate:,.0f} rows/sec)") |
||||
|
return loaded |
||||
|
|
||||
|
except Exception as e: |
||||
|
print(f"[Worker {worker_id}] ERROR: {e}") |
||||
|
raise |
||||
|
finally: |
||||
|
r.close() |
||||
|
|
||||
|
|
||||
|
def main(): |
||||
|
print("=" * 60) |
||||
|
print("Redis Bulk Loader - Sequential Phone Numbers") |
||||
|
print("=" * 60) |
||||
|
print(f"Phone Range: {PHONE_START:,} to {PHONE_END:,}") |
||||
|
print(f"Total Records: {TOTAL_RECORDS:,}\n") |
||||
|
|
||||
|
num_workers = min(NUM_WORKERS, mp.cpu_count()) |
||||
|
print(f"Using {num_workers} workers\n") |
||||
|
|
||||
|
r = redis.Redis(**REDIS_CONFIG) |
||||
|
try: |
||||
|
optimize_redis(r) |
||||
|
print("Clearing existing keys...") |
||||
|
r.flushdb() |
||||
|
finally: |
||||
|
r.close() |
||||
|
|
||||
|
start_time = time.time() |
||||
|
|
||||
|
try: |
||||
|
# ═══════════════════════════════════════════════════════ |
||||
|
# تقسیم بازه اعداد بین workers |
||||
|
# ═══════════════════════════════════════════════════════ |
||||
|
records_per_worker = TOTAL_RECORDS // num_workers |
||||
|
args = [] |
||||
|
|
||||
|
for i in range(num_workers): |
||||
|
if i < num_workers - 1: |
||||
|
start_phone = PHONE_START + (i * records_per_worker) |
||||
|
end_phone = PHONE_START + ((i + 1) * records_per_worker) - 1 |
||||
|
else: |
||||
|
# آخرین worker باقیمانده را هم میگیرد |
||||
|
start_phone = PHONE_START + (i * records_per_worker) |
||||
|
end_phone = PHONE_END |
||||
|
|
||||
|
args.append((i, start_phone, end_phone)) |
||||
|
print(f"Worker {i}: {start_phone:,} to {end_phone:,} ({end_phone - start_phone + 1:,} records)") |
||||
|
|
||||
|
print("\nStarting workers...\n") |
||||
|
|
||||
|
with ProcessPoolExecutor(max_workers=num_workers) as executor: |
||||
|
futures = [executor.submit(load_chunk_to_redis, arg) for arg in args] |
||||
|
total = 0 |
||||
|
|
||||
|
for future in as_completed(futures): |
||||
|
try: |
||||
|
total += future.result() |
||||
|
except Exception as e: |
||||
|
print(f"Worker failed: {e}") |
||||
|
|
||||
|
elapsed = time.time() - start_time |
||||
|
rate = total / elapsed if elapsed > 0 else 0 |
||||
|
remaining = (TOTAL_RECORDS - total) / rate if rate > 0 else 0 |
||||
|
percent = (total * 100) // TOTAL_RECORDS |
||||
|
|
||||
|
print(f"\n>>> Progress: {total:,}/{TOTAL_RECORDS:,} ({percent}%) | " |
||||
|
f"Speed: {rate:,.0f} rows/sec | " |
||||
|
f"ETA: {remaining / 60:.1f} min") |
||||
|
|
||||
|
print(f"\n✓ Total rows loaded: {total:,}") |
||||
|
|
||||
|
# بررسی نهایی |
||||
|
r = redis.Redis(**REDIS_CONFIG) |
||||
|
try: |
||||
|
print("\n--- Sample Results ---") |
||||
|
sample_phones = [ |
||||
|
PHONE_START, |
||||
|
PHONE_START + 10_000_000, |
||||
|
PHONE_START + 50_000_000, |
||||
|
PHONE_END |
||||
|
] |
||||
|
for phone in sample_phones: |
||||
|
value = r.get(str(phone)) |
||||
|
print(f" {phone:,} → {value}") |
||||
|
|
||||
|
final_count = r.dbsize() |
||||
|
print(f"\n✓ Final count in Redis: {final_count:,}") |
||||
|
finally: |
||||
|
r.close() |
||||
|
|
||||
|
total_time = time.time() - start_time |
||||
|
print(f"\n✓ Done! Total time: {total_time / 60:.1f} minutes") |
||||
|
print(f"✓ Average speed: {TOTAL_RECORDS / total_time:,.0f} rows/sec") |
||||
|
|
||||
|
except Exception as e: |
||||
|
print(f"\n✗ Error: {e}") |
||||
|
import traceback |
||||
|
traceback.print_exc() |
||||
|
|
||||
|
|
||||
|
if __name__ == "__main__": |
||||
|
main() |
||||
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