Neo4j Cypher 查询结构及性能优化 [英] Neo4j Cypher query structure and performance optimization
问题描述
我创建了一个 Cypher 查询动态构建器.对于复杂的情况，此构建器会生成相当大的查询，例如:
I have created a Cypher query dynamic builder. For a complex cases this builder produces a quite big queries, for example:
MATCH (parentD)-[:CONTAINS]->(childD:Decision)-[ru:CREATED_BY]->(u:User)
WHERE id(parentD) = {decisionId}
MATCH (childD)<-[:SET_FOR]-(filterValue415431:Value)-[:SET_ON]->(filterCharacteristic415431:Characteristic)
WHERE id(filterCharacteristic415431) = 415431
WITH filterValue415431, childD, ru, u
WHERE ({filterValue4154311} IN filterValue415431.value )
OR ({filterValue4154312} IN filterValue415431.value )
OR ({filterValue4154313} IN filterValue415431.value )
OR ({filterValue4154314} IN filterValue415431.value )
OR ({filterValue4154315} IN filterValue415431.value )
MATCH (childD)<-[:SET_FOR]-(filterValue415441:Value)-[:SET_ON]->(filterCharacteristic415441:Characteristic)
WHERE id(filterCharacteristic415441) = 415441
WITH filterValue415441, childD, ru, u
WHERE ({filterValue4154416} IN filterValue415441.value )
OR ({filterValue4154417} IN filterValue415441.value )
OR ({filterValue4154418} IN filterValue415441.value )
OR ({filterValue4154419} IN filterValue415441.value )
OR ({filterValue41544110} IN filterValue415441.value )
OR ({filterValue41544111} IN filterValue415441.value )
OR ({filterValue41544112} IN filterValue415441.value )
OR ({filterValue41544113} IN filterValue415441.value )
OR ({filterValue41544114} IN filterValue415441.value )
OR ({filterValue41544115} IN filterValue415441.value )
OR ({filterValue41544116} IN filterValue415441.value )
OR ({filterValue41544117} IN filterValue415441.value )
MATCH (childD)<-[:SET_FOR]-(filterValue416273:Value)-[:SET_ON]->(filterCharacteristic416273:Characteristic)
WHERE id(filterCharacteristic416273) = 416273
WITH filterValue416273, childD, ru, u
WHERE (filterValue416273.value >= {filterValue41627318})
AND (filterValue416273.value <= {filterValue41627319})
MATCH (childD)<-[:SET_FOR]-(filterValue417410:Value)-[:SET_ON]->(filterCharacteristic417410:Characteristic)
WHERE id(filterCharacteristic417410) = 417410
WITH filterValue417410, childD, ru, u
MATCH (childD)<-[:SET_FOR]-(filterValue416423:Value)-[:SET_ON]->(filterCharacteristic416423:Characteristic)
WHERE id(filterCharacteristic416423) = 416423
WITH filterValue416423, childD, ru, u
WHERE ({filterValue41642320} IN filterValue416423.value )
OR ({filterValue41642321} IN filterValue416423.value )
OR ({filterValue41642322} IN filterValue416423.value )
OR ({filterValue41642323} IN filterValue416423.value )
MATCH (childD)<-[:SET_FOR]-(filterValue415673:Value)-[:SET_ON]->(filterCharacteristic415673:Characteristic)
WHERE id(filterCharacteristic415673) = 415673
WITH filterValue415673, childD, ru, u
WHERE ({filterValue41567324} IN filterValue415673.value )
OR ({filterValue41567325} IN filterValue415673.value )
OR ({filterValue41567326} IN filterValue415673.value )
OR ({filterValue41567327} IN filterValue415673.value )
OR ({filterValue41567328} IN filterValue415673.value )
OR ({filterValue41567329} IN filterValue415673.value )
OR ({filterValue41567330} IN filterValue415673.value )
OR ({filterValue41567331} IN filterValue415673.value )
OR ({filterValue41567332} IN filterValue415673.value )
OR ({filterValue41567333} IN filterValue415673.value )
OR ({filterValue41567334} IN filterValue415673.value )
OR ({filterValue41567335} IN filterValue415673.value )
OR ({filterValue41567336} IN filterValue415673.value )
OR ({filterValue41567337} IN filterValue415673.value )
OR ({filterValue41567338} IN filterValue415673.value )
OR ({filterValue41567339} IN filterValue415673.value )
OPTIONAL MATCH (childD)<-[:VOTED_FOR]-(vg:VoteGroup)-[:VOTED_ON]->(c:Criterion)
WHERE id(c) IN {criteriaIds}
WITH childD, ru, u, vg.avgVotesWeight as weight, vg.totalVotes as totalVotes
WITH ru, u, childD , toFloat(sum(weight)) as weight, toInt(sum(totalVotes)) as totalVotes
ORDER BY weight DESC
SKIP 0 LIMIT 10
RETURN ru, u, childD AS decision, weight, totalVotes,
[ (parentD)<-[:DEFINED_BY]-(entity)<-[:COMMENTED_ON]-(comg:CommentGroup)-[:COMMENTED_FOR]->(childD) |
{entityId: id(entity), types: labels(entity), totalComments: toInt(comg.totalComments)} ] AS commentGroups,
[ (parentD)<-[:DEFINED_BY]-(c1:Criterion)<-[:VOTED_ON]-(vg1:VoteGroup)-[:VOTED_FOR]->(childD) |
{criterionId: id(c1), weight: vg1.avgVotesWeight, totalVotes: toInt(vg1.totalVotes)} ] AS weightedCriteria,
[ (parentD)<-[:DEFINED_BY]-(ch1:Characteristic)<-[:SET_ON]-(v1:Value)-[:SET_FOR]->(childD) |
{characteristicId: id(ch1), value: v1.value, valueType: ch1.valueType, visualMode: ch1.visualMode} ] AS valuedCharacteristics
现在我对表演不太满意.例如调用此查询需要 ~500 毫秒
Right now I'm not very happy with a performance. For example call on this query takes ~500ms
能否请您看看是否有机会改进此查询?
Could you please take a look and tell if there is a chance to improve this query ?
更新
这是一个几乎相同的查询，但具有不同的参数:
This is a pretty much the same query but with a different parameters:
MATCH (parentD)-[:CONTAINS]->(childD:Decision)-[ru:CREATED_BY]->(u:User)
WHERE id(parentD) = 415406
MATCH (childD)<-[:SET_FOR]-(filterValue416423:Value)-[:SET_ON]->(filterCharacteristic416423:Characteristic)
WHERE id(filterCharacteristic416423) = 416423
WITH filterValue416423, childD, ru, u
WHERE ('Adobe RGB' IN filterValue416423.value ) OR ('ECI RGB' IN filterValue416423.value )
MATCH (childD)<-[:SET_FOR]-(filterValue416273:Value)-[:SET_ON]->(filterCharacteristic416273:Characteristic)
WHERE id(filterCharacteristic416273) = 416273 WITH filterValue416273, childD, ru, u
WHERE (filterValue416273.value >= 4) AND (filterValue416273.value <= 53)
MATCH (childD)<-[:SET_FOR]-(filterValue415431:Value)-[:SET_ON]->(filterCharacteristic415431:Characteristic)
WHERE id(filterCharacteristic415431) = 415431 WITH filterValue415431, childD, ru, u
WHERE ('Compact' IN filterValue415431.value )
OR ('Compact SLR' IN filterValue415431.value )
OR ('Large SLR' IN filterValue415431.value )
OR ('Rangefinder-style mirrorless' IN filterValue415431.value )
OR ('SLR-like (bridge)' IN filterValue415431.value )
MATCH (childD)<-[:SET_FOR]-(filterValue415441:Value)-[:SET_ON]->(filterCharacteristic415441:Characteristic)
WHERE id(filterCharacteristic415441) = 415441 WITH filterValue415441, childD, ru, u
WHERE ('Brass' IN filterValue415441.value )
OR ('Carbon fiber' IN filterValue415441.value )
OPTIONAL MATCH (childD)<-[:VOTED_FOR]-(vg:VoteGroup)-[:VOTED_ON]->(c:Criterion)
WHERE id(c) IN [415414, 415415, 415412, 415426, 415411]
WITH childD, ru, u, vg.avgVotesWeight as weight, vg.totalVotes as totalVotes
WITH ru, u, childD , toFloat(sum(weight)) as weight, toInt(sum(totalVotes)) as totalVotes
ORDER BY weight DESC
SKIP 0 LIMIT 10
RETURN ru, u, childD AS decision, weight, totalVotes,
[ (parentD)<-[:DEFINED_BY]-(entity)<-[:COMMENTED_ON]-(comg:CommentGroup)-[:COMMENTED_FOR]->(childD) |
{entityId: id(entity), types: labels(entity), totalComments: toInt(comg.totalComments)} ] AS commentGroups,
[ (parentD)<-[:DEFINED_BY]-(c1:Criterion)<-[:VOTED_ON]-(vg1:VoteGroup)-[:VOTED_FOR]->(childD) |
{criterionId: id(c1), weight: vg1.avgVotesWeight, totalVotes: toInt(vg1.totalVotes)} ] AS weightedCriteria,
[ (parentD)<-[:DEFINED_BY]-(ch1:Characteristic)<-[:SET_ON]-(v1:Value)-[:SET_FOR]->(childD) |
{characteristicId: id(ch1), value: v1.value, valueType: ch1.valueType, visualMode: ch1.visualMode} ] AS valuedCharacteristics
密码版本:CYPHER 3.1，规划器:成本，运行时间:解释.390 毫秒内总共有 646192 次数据库命中.
Cypher version: CYPHER 3.1, planner: COST, runtime: INTERPRETED. 646192 total db hits in 390 ms.
更新
这是:schema
Indexes
ON :Characteristic(lowerName) ONLINE
ON :CharacteristicGroup(lowerName) ONLINE
ON :Criterion(lowerName) ONLINE
ON :CriterionGroup(lowerName) ONLINE
ON :Decision(lowerName) ONLINE
ON :FlagType(name) ONLINE (for uniqueness constraint)
ON :HistoryValue(originalValue) ONLINE
ON :Permission(code) ONLINE (for uniqueness constraint)
ON :Role(name) ONLINE (for uniqueness constraint)
ON :User(email) ONLINE (for uniqueness constraint)
ON :User(username) ONLINE (for uniqueness constraint)
ON :Value(value) ONLINE
Constraints
ON ( flagtype:FlagType ) ASSERT flagtype.name IS UNIQUE
ON ( permission:Permission ) ASSERT permission.code IS UNIQUE
ON ( role:Role ) ASSERT role.name IS UNIQUE
ON ( user:User ) ASSERT user.email IS UNIQUE
ON ( user:User ) ASSERT user.username IS UNIQUE
更新
我已按照以下答案中的建议优化了查询:
I have optimized the query as suggest at the answer below:
MATCH (parentD)-[:CONTAINS]->(childD:Decision)
WHERE id(parentD) = 415406
MATCH (childD)<-[:SET_FOR]-(filterValue416423)-[:SET_ON]->(filterCharacteristic416423)
WHERE id(filterCharacteristic416423) = 416423
WITH DISTINCT filterValue416423, childD
WHERE ('Adobe RGB' IN filterValue416423.value ) OR ('ECI RGB' IN filterValue416423.value )
MATCH (childD)<-[:SET_FOR]-(filterValue416273)-[:SET_ON]->(filterCharacteristic416273)
WHERE id(filterCharacteristic416273) = 416273
WITH DISTINCT childD, filterValue416273
WHERE (filterValue416273.value >= 4) AND (filterValue416273.value <= 53)
MATCH (childD)<-[:SET_FOR]-(filterValue415431)-[:SET_ON]->(filterCharacteristic415431)
WHERE id(filterCharacteristic415431) = 415431
WITH DISTINCT childD, filterValue415431
WHERE ('Compact' IN filterValue415431.value )
OR ('Compact SLR' IN filterValue415431.value )
OR ('Large SLR' IN filterValue415431.value )
OR ('Rangefinder-style mirrorless' IN filterValue415431.value )
OR ('SLR-like (bridge)' IN filterValue415431.value )
MATCH (childD)<-[:SET_FOR]-(filterValue415441)-[:SET_ON]->(filterCharacteristic415441)
WHERE id(filterCharacteristic415441) = 415441
WITH DISTINCT childD, filterValue415441
WHERE ('Brass' IN filterValue415441.value )
OR ('Carbon fiber' IN filterValue415441.value )
OPTIONAL MATCH (childD)<-[:VOTED_FOR]-(vg:VoteGroup)-[:VOTED_ON]->(c:Criterion)
WHERE id(c) IN [415414, 415415, 415412, 415426, 415411]
WITH DISTINCT * MATCH (childD)-[ru:CREATED_BY]->(u:User)
WITH DISTINCT childD, ru, u, vg.avgVotesWeight as weight, vg.totalVotes as totalVotes
WITH DISTINCT ru, u, childD , toFloat(sum(weight)) as weight, toInt(sum(totalVotes)) as totalVotes
ORDER BY weight DESC
SKIP 0 LIMIT 10
RETURN ru, u, childD AS decision, weight, totalVotes,
[ (parentD)<-[:DEFINED_BY]-(entity)<-[:COMMENTED_ON]-(comg:CommentGroup)-[:COMMENTED_FOR]->(childD) |
{entityId: id(entity), types: labels(entity), totalComments: toInt(comg.totalComments)} ] AS commentGroups,
[ (parentD)<-[:DEFINED_BY]-(c1:Criterion)<-[:VOTED_ON]-(vg1:VoteGroup)-[:VOTED_FOR]->(childD) |
{criterionId: id(c1), weight: vg1.avgVotesWeight, totalVotes: toInt(vg1.totalVotes)} ] AS weightedCriteria,
[ (parentD)<-[:DEFINED_BY]-(ch1:Characteristic)<-[:SET_ON]-(v1)-[:SET_FOR]->(childD) |
{characteristicId: id(ch1), value: v1.value, valueType: ch1.valueType, visualMode: ch1.visualMode} ] AS valuedCharacteristics
配置文件输出:
使用 DISTINCT childD 查询的工作速度很慢，没有更好的但离完美还有很远
With DISTINCT childD the query works pretty slow, without much better but stil so far from perfect
再试一次
PROFILE MATCH (parentD)-[:CONTAINS]->(childD:Decision)
WHERE id(parentD) = 415406
MATCH (childD)<-[:SET_FOR]-(filterValue416423)-[:SET_ON]->(filterCharacteristic416423)
USING JOIN ON childD
WHERE id(filterCharacteristic416423) = 416423
AND ('Adobe RGB' IN filterValue416423.value ) OR ('ECI RGB' IN filterValue416423.value )
WITH DISTINCT childD
MATCH (childD)<-[:SET_FOR]-(filterValue416273)-[:SET_ON]->(filterCharacteristic416273)
USING JOIN ON childD
WHERE id(filterCharacteristic416273) = 416273 AND (filterValue416273.value >= 4) AND (filterValue416273.value <= 53)
WITH DISTINCT childD
MATCH (childD)<-[:SET_FOR]-(filterValue415431)-[:SET_ON]->(filterCharacteristic415431)
USING JOIN ON childD
WHERE id(filterCharacteristic415431) = 415431
AND ('Compact' IN filterValue415431.value )
OR ('Compact SLR' IN filterValue415431.value )
OR ('Large SLR' IN filterValue415431.value )
OR ('Rangefinder-style mirrorless' IN filterValue415431.value )
OR ('SLR-like (bridge)' IN filterValue415431.value )
WITH DISTINCT childD
MATCH (childD)<-[:SET_FOR]-(filterValue415441)-[:SET_ON]->(filterCharacteristic415441)
USING JOIN ON childD
WHERE id(filterCharacteristic415441) = 415441
AND ('Brass' IN filterValue415441.value )
OR ('Carbon fiber' IN filterValue415441.value )
OPTIONAL MATCH (childD)<-[:VOTED_FOR]-(vg:VoteGroup)-[:VOTED_ON]->(c:Criterion)
WHERE id(c) IN [415414, 415415, 415412, 415426, 415411]
WITH DISTINCT * MATCH (childD)-[ru:CREATED_BY]->(u:User)
WITH DISTINCT childD, ru, u, vg.avgVotesWeight as weight, vg.totalVotes as totalVotes
WITH DISTINCT ru, u, childD , toFloat(sum(weight)) as weight, toInt(sum(totalVotes)) as totalVotes
ORDER BY weight DESC
SKIP 0 LIMIT 10
RETURN childD
推荐答案
您的查询的主要问题是您基本上进行了大量检查，而且行会变得异常.因此，这里有一些技巧可以减少您在每次 MATCH 中生成的行数.
The main problem with your query, is that you are basically doing a lot of checks, with rows running wild. So here are some tips to reduce how many rows you are generating at each MATCH.
1) 除非您需要重复，否则请使用 WITH DISTINCT 而不仅仅是 WITH.WITH 可以创建重复行(因为您只截断了一个列)，并且您处理的每个重复行都浪费了时间和额外的 DB 命中.(即，您删除的每个过滤器列都会添加重复的行)
1) Unless you NEED duplicates, use WITH DISTINCT instead of just WITH. WITH can create duplicate rows (because you only cut off a column), and every duplicate row you process is wasted time and extra DB hits. (Namely, every filter column you drop adds duplicate rows)
2) :Value.value 被重载.它没有语义意义，甚至不能保证该值是任何类型的.这意味着每个 :Value 检查都必须出去并接触一堆与您搜索的内容无关的 :Value 节点.因此，随着附加 :Value 节点数量的增加，找到合适的节点的成本就越高(如果它可以被编入索引，这样它就可以找到正确的 :Value，然后查看它连接到什么节点，这样成本会更低).如果您无法更改您正在使用的架构，这将无济于事，而架构，我的意思是您的数据/关系是如何设置的).
2) :Value.value is overloaded. It has no semantic meaning, and the value isn't even guaranteed to be any kind of type. That means every :Value check has to go out and touch a bunch of :Value nodes that have nothing to do with what your searching for. So as the number of attached :Value nodes increases, the more expensive it becomes to find the right one (This is less expensive if it could be indexed, so that it could just find the right :Value, and see what it is connected to. This doesn't help if you can't change the schema you're working with, and by schema, I mean how your data/relationships are setup).
3) 只检查您需要检查的内容.说 (a:A)-[:TO]->(b:B) 似乎更有效，但如果所有 [:TO] 都来自 :A 到 :B，Neo4j 现在必须验证第一个节点是一个:A，第二个节点是一个:B.Cypher 不知道什么是隐式正确，所以它必须进行检查，但是这些冗余检查中的每一个都必须出去并针对每一行命中 DB.所以最好说 (a)-[:TO]->(b).
3) Only check what you need to check. It might seem more efficient to say (a:A)-[:TO]->(b:B), but if all [:TO] are from :A to :B, Neo4j now has to verify that the first node is an :A and the second node is a :B. Cypher doesn't know what is implicitly true, so it has to do the check, but each of these redundant checks has to go out and hit the DB for every row. So it is better to say (a)-[:TO]->(b).
4) 限制变量范围.在这里，您在开头匹配 -[ru:CREATED_BY]->(u:User) 但直到最后才使用它，没有过滤器.这将您拥有的行数乘以每个决定的 -[ru:CREATED_BY]->(u:User) 的数量，所有必须在进一步匹配中检查.除非 -[ru:CREATED_BY]->(u:User) 以某种方式极大地限制了匹配的决策(或者每个决策只能有一个)，否则请在最后匹配此支持信息.
4) Limit variable scope. Here, you match -[ru:CREATED_BY]->(u:User) at the beginning but than don't use it til the end, with no filters. This multiplies how many rows you have by the number of -[ru:CREATED_BY]->(u:User) on each decision, that ALL have to be checked in the further matches. Unless -[ru:CREATED_BY]->(u:User) somehow greatly limits the matched decisions (or there can only be one per decision), match this support information at the end.
5) 将过滤器从最强到最弱排序(如果可以的话).尽早切割尽可能多的行.
5) Order your filters from strongest to weakest (if you can). to cut as many rows as early as possible.
6) 最小化行的技巧.拉起的每一行都会使查询中的以下步骤变得更加困难，因此尽量减少查询中的行.如果您使用 OR 来组合不相关但相似的列查询(例如所有具有条件 A 的组织或具有条件 B 的组织)并且这两个查询的工作只会使另一半的事情变得更加昂贵，那么使用 UNION 可能会更好合并更小、更快的查询的结果(并且 UNION 可以并行运行直到合并结果).请注意，像 [1,2,3] 中的 WHERE org.id 这样的简单查询仍然比 UNION 快，因为所有工作都可以在一次查找中完成.
6) Tricks to minimize rows. Each row pulled up makes the following steps in the query have to work that much harder, so minimize rows in queries. If you are using OR to combine unrelated, but similar columns queries (like all orgs with conditions A or orgs with conditions B) and the work of the two queries just make things more expensive for the other half, it might be better to use UNION to combine the results of smaller, faster queries (and UNION can run in parallel up to the merge results). Note that simple queries like WHERE org.id in [1,2,3] are still faster than UNION, since the work can all be done in one lookup.
除了联合之外，如果您正在收集没有过滤的节点，您可以使用 collect(column) 将重复项"减少到 1 行，而不是 UNWIND(列)作为列末尾的列查询以获取您的行！(这里的列指的是变量名)
Aside from union, if you are collecting nodes that you don't filter on, you can use collect(column) to reduce 'duplicates' down to 1 row, and than UNWIND (column) as column at the end of the query to get your rows back! (column here referring to variable name)
7) 在 1 个节点上做很多过滤?Cypher 有 USING提示！提示 USING JOIN ON column 告诉 Cypher，使用更多的起始叶子并加入它们可能会更有效地进行匹配.因此，在每个匹配项上使用 USING JOIN ON childD 将告诉 Cypher 并行执行所有过滤器，并使用所有过滤器的重叠行.请注意，USING 只是您告诉 Cypher相信我，如果我们尝试这样做，这应该会更快"，如果您错了，这实际上会使查询变得更糟.(使用 JOIN 应该有助于使大型查询更加并行)
7) Doing a lot of filters on 1 node? Cypher has USING hints for that! The hint USING JOIN ON column tells Cypher that it will probably be more efficient doing this match with more starting leafs and joining them. So using USING JOIN ON childD on each match will tell Cypher to do all the filters in parallel, and use the overlapping rows of all of them. Note that USINGs are just you telling Cypher "trust me, this should go faster if we try doing this" which can actually make the query worse if you are wrong. (USING JOIN should be useful though for making large queries more parallel though)
更新:
首先，注意 node.id = "constant" AND node.value = "constant" OR node.id = "constant2" AND node.value = "constant2" vs node.value = map[node.id].第一个查询能够对节点查找进行节点过滤，而后者必须过滤所有已经查找过的节点.没有对该查找进行先前过滤，这意味着地图必须拉入所有节点.虽然地图提供了某种程度的(有争议的)简单性/灵活性，但它是过滤节点效率最低的方法之一.
UPDATE:
First, a note on node.id = "constant" AND node.value = "constant" OR node.id = "constant2" AND node.value = "constant2" vs node.value = map[node.id]. The first query is able to do node filtering on node lookup, while the later has to filter through all of the nodes that where already looked up. Without previous filtering on that lookup, that means the map has to pull in all nodes. While the map offers some level of (arguable) simplicity/flexibility, it is one of the least efficient ways to filter nodes.
第二，您现在查询的大问题是 :Value 超载，而且您无法通过 ID 找到它.:Value 应该是一个关系，或者有一个索引 ID 字段，这样你就不必触摸 ALL <-[:SET_FOR]- 和 -[:SET_ON]->.我认为使用 Join 提示至少会使 SET_FOR 具有更高的优先级，这似乎是两者中效率更高的.
Second, The big problem with your query now, is the :Value is super overloaded, and you aren't finding it by ID. :Value should be a relationship, or have an indexed ID field so that you don't have to touch ALL <-[:SET_FOR]- and -[:SET_ON]->. Using the Join hint I think will at least make SET_FOR higher priority, which appears to be the more efficient of the two.
这是我更有效地重写 PROFILE 查询的尝试.(v1)
Here is my attempt to rewrite the PROFILE query more efficiently. (v1)
MATCH (parentD)-[:CONTAINS]->(childD:Decision)
WHERE id(parentD) = 415406
MATCH (childD)<-[:SET_FOR]-(filterValue416423)-[:SET_ON]->(filterCharacteristic416423)
USING JOIN ON childD
WHERE id(filterCharacteristic416423) = 416423
WHERE ('Adobe RGB' IN filterValue416423.value ) OR ('ECI RGB' IN filterValue416423.value )
WITH DISTINCT childD
MATCH (childD)<-[:SET_FOR]-(filterValue416273)-[:SET_ON]->(filterCharacteristic416273)
USING JOIN ON childD
WHERE id(filterCharacteristic416273) = 416273 AND (filterValue416273.value >= 4) AND (filterValue416273.value <= 53)
WITH DISTINCT childD
MATCH (childD)<-[:SET_FOR]-(filterValue415431)-[:SET_ON]->(filterCharacteristic415431)
USING JOIN ON childD
WHERE id(filterCharacteristic415431) = 415431
WHERE ('Compact' IN filterValue415431.value )
OR ('Compact SLR' IN filterValue415431.value )
OR ('Large SLR' IN filterValue415431.value )
OR ('Rangefinder-style mirrorless' IN filterValue415431.value )
OR ('SLR-like (bridge)' IN filterValue415431.value )
WITH DISTINCT childD
MATCH (childD)<-[:SET_FOR]-(filterValue415441)-[:SET_ON]->(filterCharacteristic415441)
USING JOIN ON childD
WHERE id(filterCharacteristic415441) = 415441
WHERE ('Brass' IN filterValue415441.value )
OR ('Carbon fiber' IN filterValue415441.value )
OPTIONAL MATCH (childD)<-[:VOTED_FOR]-(vg:VoteGroup)-[:VOTED_ON]->(c:Criterion)
WHERE id(c) IN [415414, 415415, 415412, 415426, 415411]
WITH DISTINCT * MATCH (childD)-[ru:CREATED_BY]->(u:User)
WITH DISTINCT childD, ru, u, vg.avgVotesWeight as weight, vg.totalVotes as totalVotes
WITH DISTINCT ru, u, childD , toFloat(sum(weight)) as weight, toInt(sum(totalVotes)) as totalVotes
ORDER BY weight DESC
SKIP 0 LIMIT 10
RETURN ru, u, childD AS decision, weight, totalVotes,
[ (parentD)<-[:DEFINED_BY]-(entity)<-[:COMMENTED_ON]-(comg:CommentGroup)-[:COMMENTED_FOR]->(childD) |
{entityId: id(entity), types: labels(entity), totalComments: toInt(comg.totalComments)} ] AS commentGroups,
[ (parentD)<-[:DEFINED_BY]-(c1:Criterion)<-[:VOTED_ON]-(vg1:VoteGroup)-[:VOTED_FOR]->(childD) |
{criterionId: id(c1), weight: vg1.avgVotesWeight, totalVotes: toInt(vg1.totalVotes)} ] AS weightedCriteria,
[ (parentD)<-[:DEFINED_BY]-(ch1:Characteristic)<-[:SET_ON]-(v1)-[:SET_FOR]->(childD) |
{characteristicId: id(ch1), value: v1.value, valueType: ch1.valueType, visualMode: ch1.visualMode} ] AS valuedCharacteristics
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