我们面临着将大型数据集从 postgres(备份或其他)迁移到 elasticsearch 的问题。
我们有类似这样的架构
+---------------+--------------+------------+-----------+
| user_id | created_at | latitude | longitude |
+---------------+--------------+------------+-----------+
| 5 | 23.1.2015 | 12.49 | 20.39 |
+---------------+--------------+------------+-----------+
| 2 | 23.1.2015 | 12.42 | 20.32 |
+---------------+--------------+------------+-----------+
| 2 | 24.1.2015 | 12.41 | 20.31 |
+---------------+--------------+------------+-----------+
| 5 | 25.1.2015 | 12.45 | 20.32 |
+---------------+--------------+------------+-----------+
| 1 | 23.1.2015 | 12.43 | 20.34 |
+---------------+--------------+------------+-----------+
| 1 | 24.1.2015 | 12.42 | 20.31 |
+---------------+--------------+------------+-----------+
而且我们能够通过 created_at 找到最新的位置,这要归功于 SQL 中的 rank 函数
... WITH locations AS (
select user_id, lat, lon, rank() over (partition by user_id order by created_at) as r
FROM locations)
SELECT user_id, lat, lon FROM locations WHERE r = 1
并且结果仅为每个用户最新创建的位置:
+---------------+--------------+------------+-----------+
| user_id | created_at | latitude | longitude |
+---------------+--------------+------------+-----------+
| 2 | 24.1.2015 | 12.41 | 20.31 |
+---------------+--------------+------------+-----------+
| 5 | 25.1.2015 | 12.45 | 20.32 |
+---------------+--------------+------------+-----------+
| 1 | 24.1.2015 | 12.42 | 20.31 |
+---------------+--------------+------------+-----------+
将数据导入elasticsearch后,我们的文档模型如下所示:
{
"location" : { "lat" : 12.45, "lon" : 46.84 },
"user_id" : 5,
"created_at" : "2015-01-24T07:55:20.606+00:00"
}
etc...
我正在 elasticsearch 查询中寻找此 SQL 查询的替代方案,我认为这一定是可能的,但我还没有找到。
最佳答案
您可以使用 field collapsing
结合 inner_hits
来实现这一点。
{
"collapse": {
"field": "user_id",
"inner_hits": {
"name": "order by created_at",
"size": 1,
"sort": [
{
"created_at": "desc"
}
]
}
},
}
详细文章:https://blog.francium.tech/sql-window-function-partition-by-in-elasticsearch-c2e3941495b6
关于sql - 在 elasticsearch 中从 postgresql 对分区进行排名,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/32603206/