开源搜索组件whoosh笔记
coding=utf-8
import os,json,time
from whoosh.index import create_in
from whoosh.fields import *
from jieba.analyse import ChineseAnalyzer
from whoosh.qparser import QueryParser
from whoosh import qparser, scoring
from whoosh import index
import MySQLdb as mdb
reload(sys)
sys.setdefaultencoding('utf8')
start = time.time()
con = mdb.connect('localhost','root','ab24562660','kznews',charset='utf8',unix_socket='/tmp/mysql.sock')
def new_index_sql():
# 按照schema定义信息,增加需要建立索引的文档
# 注意:字符串格式需要为unicode格式
writer = ix.writer(limitmb=256,procs=4)
cur = con.cursor()
n = 0
a = cur.execute("select count(*) from xinwen ")
number = int(cur.fetchone()[0])
with con:
cur.execute("select id,cid,title from xinwen")
numrows = int(cur.rowcount)
for i in range(numrows):
row = cur.fetchone()
pid = row[0]
cid = row[1]
title = row[2]
writer.add_document(title=title, pid=pid, cid=cid)
n += 1
percent=float(n)*100/float(number)
sys.stdout.write("-----------> 完成百分比:%.2f" % percent)
sys.stdout.write("%\r")
sys.stdout.flush()
writer.commit()
sys.stdout.flush()
def search_index(words):
with ix.searcher() as s:
qp = QueryParser('title',schema=ix.schema)
for word in words:
q = qp.parse(u'%s' % word)
results = s.search(q,limit=20)
for i in results:
print word + "----->" + i["title"],i.highlights("title"),i.score
使用结巴中文分词
analyzer = ChineseAnalyzer()
创建schema, stored为True表示能够被检索
schema = Schema(
title=TEXT(stored=True, analyzer=analyzer),
pid=NUMERIC(stored=True),
cid=NUMERIC(stored=True),
)
存储schema信息至'indexdir'目录下
indexdir = 'xinwen_search/'
if not os.path.exists(indexdir):
os.mkdir(indexdir)
try:
ix=index.open_dir(indexdir)
print '>>>>>>>> 已创建索引 <<<<<<<<<<'
except:
print '>>>>>>>> 未创建索引 <<<<<<<<<<'
ix = create_in(indexdir, schema)
new_index_sql()
words = ["太阳","下雨","月亮","螺丝","刀把","挖掘机"]
search_index(words)
end = time.time()
print "完成时间: %f s" % (end - start)
在创建索引的速度上真心慢的一逼,200万条标题,xunsearch创建索引大概花半小时,whoosh花了一个多小时。
但是创建索引速度慢不要紧,大不了在晚上运行,只要查询索引速度不慢就好了。
况且,whoosh索引数据的体积很小,200万条标题,创建索引后只有不到700M。
而xunsearch创建完后居然有几个G,太尼玛占空间了。但是看了文档,估计whoosh在搜索相关性和搜索灵活性上比不过xunsearch。则实际情况,相机选择。
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