import moxing as mox
mox.file.copy('obs://obs-aigallery-zc/GES/ges4jupyter/beta/ges4jupyter.py', 'ges4jupyter.py')
mox.file.copy('obs://obs-aigallery-zc/GES/ges4jupyter/beta/ges4jupyter.html', 'ges4jupyter.html')

from ges4jupyter import GESConfig, GES4Jupyter, read_csv_config
eip = ''
project_id = ''
graph_name = ''
iam_url = ''
user_name = ''
password = ''
domain_name = ''
project_name = ''
port = 80
eip, project_id, graph_name, iam_url, user_name, password, domain_name, project_name, port = read_csv_config('cn_north_4_graph.csv')
config = GESConfig(eip, project_id, graph_name, 
                    iam_url = iam_url, 
                    user_name = user_name, 
                    password = password, 
                    domain_name = domain_name,
                    project_name = project_name,
                    port = port)
ges_util = GES4Jupyter(config, True);

import time
def wait_job_finish(util, job_id, max_loop):
    job_result = util.get_job(job_id)
    if 'errorCode' not in job_result:
        for i in range(max_loop):
            if job_result['status'] == 'success':
                break
            else:
                time.sleep(1)
                job_result = util.get_job(job_id)
    print(job_result)

job_id = ges_util.build_vertex_index()
wait_job_finish(ges_util, job_id, 100)
job_id = ges_util.build_edge_index()
wait_job_finish(ges_util, job_id, 100)

import time
body = ges_util.generate_schema_structure()
job_id = body["jobId"]
print('開始構(gòu)造schema結(jié)構(gòu):')
wait_job_finish(ges_util, job_id, 100)
print('schema結(jié)構(gòu)構(gòu)造完成')
cypher_result = ges_util.cypher_query("call db.schema()",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result, candidate_title = ['description', 'name'])

match (n)-[:KNOWS]->(a)-[:KNOWS]->(b) where id(n)='p367' return distinct b

match (n)-[:KNOWS]->(a) where id(n)='p367' with n, collect(a) as neighbor
match (n)-[:KNOWS]->(a)-[:KNOWS]->(b) 
where not (b in neighbor)
return b

match (n) where id(n)='p367'
match (n)-[:KNOWS*2..2]->(b)
where not (n)-[:KNOWS]->(b)
return id(b) limit 10
cypher_result = ges_util.cypher_query("""
match (n) where id(n)='p367' 
match (n)-[:KNOWS*2..2]->(b) where not (n)-[:KNOWS]->(b) 
return id(b) limit 10""",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result)

match (n:Person) where id(n)='p933' 
match (n)-[r]->(m) where not (m)-[:HAS_INTEREST]-() return id(m)

match (n) where id(n)='p367' 
with [(n)-[:KNOWS*2..2]->(b)|id(b)] as hop2,  [(n)-[:KNOWS]->(b)|id(b)] as hop1
return [x in hop2 where not x in hop1|x] limit 10

match (n) where id(n)='p367' 
with [(n)-[:KNOWS*3..3]->(b)|id(b)] as hop3,  [(n)-[:KNOWS*1..2]->(b)|id(b)] as hop2
return size([x in hop3 where not x in hop2|x])
cypher_result = ges_util.cypher_query("""
match (n) where id(n)='p367' 
with [(n)-[:KNOWS*3..3]->(b)|id(b)] as hop3,  [(n)-[:KNOWS*1..2]->(b)|id(b)] as hop2 
return size([x in hop3 where not x in hop2|x])""",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result, boxHeight=200)

?

同時(shí)這種子查詢后續(xù)步驟也可以跟隨一些過濾條件，進(jìn)行各類統(tǒng)計(jì)操作，如上述提到的潛在二度人脈分析：

match (n:Person) where id(n) in ['p367','p13194139534836','p932','p4398046512206','p6597069767359'] 
with n, [(n)-[:KNOWS*2..2]->(m) where not (n)-->(m)|m] as recSet
return id(n) as key, 
    size([x in recSet where x.gender='male']) as maleNumber,
    size([x in recSet where x.gender='female']) as femaleNumber
cypher_result = ges_util.cypher_query("""
match (n:Person) where id(n) in ['p367','p13194139534836','p932','p4398046512206','p6597069767359'] 
with n, [(n)-[:KNOWS*2..2]->(m) where not (n)-->(m)|m] as recSet 
return id(n), size([x in recSet where x.gender='male']),size([x in recSet where x.gender='female'])
""",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result, boxHeight=200)

?

下列元素出現(xiàn)在with子句中，描述了一個(gè)子查詢：

[(n)-[:KNOWS*2..2]->(m) where some-condition|m] as recSet

這里會對每個(gè)遍歷到的n，都進(jìn)行二跳查詢， 取二跳查詢的末端節(jié)點(diǎn)m，然后組裝成一個(gè)列表。

注意到where條件中，使用了剛剛提到的條件子查詢：

where not (n)-->(m)

這里條件使用where條件，對子查詢的結(jié)果進(jìn)行了過濾，且過濾時(shí)，是將一個(gè)Graph Pattern作為的過濾條件，最后使用豎線進(jìn)行投影。

在return子句中，使用了Cypher中List Comprehension的語法，進(jìn)行列表過濾,并獲取大小：

return id(n) as key, 
    size([x in recSet where x.gender='male']) as maleNumber,
    size([x in recSet where x.gender='female']) as femaleNumber

支撐子查詢結(jié)果作為中間結(jié)果的，是RollUpApply算子，可以通過explain看到其在查詢計(jì)劃中發(fā)揮價(jià)值：

cypher_result = ges_util.cypher_query("""explain 
match (n:Person) where id(n) in ['p367','p13194139534836','p932','p4398046512206','p6597069767359'] 
return n, [(n)-[:KNOWS*2..2]->(m) where not (n)-->(m)|m] as recSet""",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result, boxHeight=200)

?

為了可視化演示效果，可視化時(shí)同步打印了“朋友”和“INTEREST”邊。

同樣的，也可以使用RollUpApply+Limit對每跳做PerNodeLimit，例如統(tǒng)計(jì)和小明的朋友有共同興趣愛好的朋友，每個(gè)頂點(diǎn)每跳最多找3個(gè)點(diǎn),最后一跳每個(gè)點(diǎn)最多找1個(gè)點(diǎn)：

match (n:Person) where id(n)='p367' 
match (n)-[r]->(m) with m limit 3 
with m,[(m)<-[r1:HAS_INTEREST]-(a)|a][0..3] as interests 
unwind interests as interest 
with interest, [(interest)-[r1:HAS_INTEREST]->(a) where not (a)--(m)|[r1,a]][0..1] as soulMate
return *

?

match (n:Person) where id(n) in ['p367','p13194139534836','p932','p4398046512206','p6597069767359'] 
with n limit 10
match (m:Person{lastName:n.lastName}) return n.lastName, m.firstName

cypher_result = ges_util.cypher_query("""explain 
match (n:Person) where id(n) in ['p367','p13194139534836','p932','p4398046512206','p6597069767359'] 
with n limit 10
match (m:Person{lastName:n.lastName}) return n.lastName, m.firstName""",formats=['row','graph']);
ges_util.format_cypher_result(cypher_result)

?

由于不同的n，其n.lastName的值是不固定的，所以需要針對每個(gè)n，去做match (m:Person{lastName:n.lastName})這樣的查詢，因此需要使用Apply子查詢算子支撐這樣的語句。

總結(jié)借助子查詢進(jìn)行局部遍歷是圖查詢中的常用操作，將子查詢作為過濾條件或者中間結(jié)果輔助查詢，可以滿足某些業(yè)務(wù)場景下對查詢局部有限制的訴求，

如文中提到的社交網(wǎng)絡(luò)分析，再如股權(quán)關(guān)系中穿透層數(shù)分析、裝備制造和配置管理（IT設(shè)備管理）領(lǐng)域依賴識別和變更影響分析等。

此外，由于Cypher以行的形式組織數(shù)據(jù)，某些情況下使用子查詢可以節(jié)省中間結(jié)果產(chǎn)生，加速Cypher查詢的執(zhí)行。

當(dāng)然，使用更高效的API（如GES產(chǎn)品中有多跳過濾API)或者使用非行存的查詢執(zhí)行引擎也是可選的解決方案。