Python 调用 elasticsearch 的 bulk 接口批量插入数据出现内存泄露，导致 OOM

数据导入脚本如下

import time import sys from elasticsearch import Elasticsearch from elasticsearch.helpers import bulk reload(sys) sys.setdefaultencoding('utf-8') def set_mapping(es, index_name = "content_engine", doc_type_name = "en"): my_mapping = { "en": { "properties": { "a": { "type": "string" }, "b": { "type": "string" } } } } create_index = es.indices.create(index = index_name,body = my_mapping) mapping_index = es.indices.put_mapping(index = index_name, doc_type = doc_type_name, body = my_mapping) if create_index["acknowledged"] != True or mapping_index["acknowledged"] != True: print "Index creation failed..." def set_data(es, input_file, index_name = "content_engine", doc_type_name="en"): i = 0 count = 0 ACTIOnS= [] for line in open(input_file): fields = line.replace("\r\n", "").replace("\n", "").split("----") if len(fields) == 2: a, b = fields else: continue action = { "_index": index_name, "_type": doc_type_name, "_source": { "a": a, "b": b, } } i += 1 ACTIONS.append(action) if (i == 500000): success, _ = bulk(es, ACTIONS, index = index_name, raise_on_error = True) count += success i = 0 ACTIOnS= [] success, _ = bulk(es, ACTIONS, index = index_name, raise_on_error=True) count += success print("insert %s lines" % count) if __name__ == '__main__': es = Elasticsearch(hosts=["127.0.0.1:9200"], timeout=5000) set_mapping(es) set_data(es,sys.argv[1]) 

数据大概 5 个 G 吧，机器配置虚拟机 24G 内存，刚开始无内存泄露现象，这个 Python 脚本的进程内存一直保持 1G 左右的占用，当插入 1600 ｗ，内存开始持续飙升，最后达到 22G ，导致触发 OOM 机制， Python 进程被内核 kill ，差点怀疑人生。。大家在遇到 Python 内存泄露都是怎么定位的？