At present, the application of vlog in the code is quite confusing.
It is inherited from impala VLOG_XX format, and there is also VLOG(number) format.
VLOG(number) format does not have a unified specification, so this pr standardizes the use of VLOG
We make all MemTrackers shared, in order to show MemTracker real-time consumptions on the web.
As follows:
1. nearly all MemTracker raw ptr -> shared_ptr
2. Use CreateTracker() to create new MemTracker(in order to add itself to its parent)
3. RowBatch & MemPool still use raw ptrs of MemTracker, it's easy to ensure RowBatch & MemPool destructor exec
before MemTracker's destructor. So we don't change these code.
4. MemTracker can use RuntimeProfile's counter to calc consumption. So RuntimeProfile's counter need to be shared
too. We add a shared counter pool to store the shared counter, don't change other counters of RuntimeProfile.
Note that, this PR doesn't change the MemTracker tree structure. So there still have some orphan trackers, e.g. RowBlockV2's MemTracker. If you find some shared MemTrackers are little memory consumption & too time-consuming, you could make them be the orphan, then it's fine to use the raw ptr.
#3479
Here I try to explain the cause of the problem and how to fix it.
**The Cause of The problem**
Take the case in issue(#3479 ) as an example:
The general results are as follows:
```
GET table/_doc/_search
{"query":{"match_all":{}},"stored_fields":"_none_","docvalue_fields":["k1"],"sort":["_doc"],"size":100}
{
"took": 6,
"timed_out": false,
"_shards": {
……
},
"hits": {
"total": 3,
"max_score": null,
"hits": [
{
"_index": "table",
"_score": null,
"sort": [
0
]
},
{
"_index": "table",
"_score": null,
"fields": {
"k1": [
"kkk1"
]
},
"sort": [
0
]
},
{
"_index": "table",
"_score": null,
"sort": [
0
]
}
]
}
}
```
But in Doris on ES，Be fetched data parallelly on all shards, and use `filter_path` to reduce the network cost. The process will be as follows:
```
GET table/_doc/_search?preference=_shards:1&filter_path=_scroll_id,hits.hits._source,hits.total,_id,hits.hits._source.fields,hits.hits.fields
{"query":{"match_all":{}},"stored_fields":"_none_","docvalue_fields":["k1"],"sort":["_doc"],"size":100}
{
"hits": {
"total": 0
}
}
GET table/_doc/_search?preference=_shards:2&filter_path=_scroll_id,hits.hits._source,hits.total,_id,hits.hits._source.fields,hits.hits.fields
{"query":{"match_all":{}},"stored_fields":"_none_","docvalue_fields":["k1"],"sort":["_doc"],"size":100}
{
"hits": {
"total": 1
}
}
GET table/_doc/_search?preference=_shards:3&filter_path=_scroll_id,hits.hits._source,hits.total,_id,hits.hits._source.fields,hits.hits.fields
{"query":{"match_all":{}},"stored_fields":"_none_","docvalue_fields":["k1"],"sort":["_doc"],"size":100}
{
"hits": {
"total": 1,
"hits": [
{
"fields": {
"k1": [
"kkk1"
]
}
}
]
}
}
```
*Scan-Worker On BE which processed result of shard2 will failed.*
**The reasons are as follows:**
1. "filter_path" causes the hits.hits object not exist.
2. In the current implementation, if there are some data rows（total > 0）, the hits.hits. object must be an array
**How To Fix it**
Two Method:
1. modify "filter_path" to contain the hits.
Pros: Fixed Code is very simple
Cons: More network cost
2. Deal with the case where fields are missing in a batch.
Pros: No loss of performance
Cons: Code is more complex
Performance first, I use Method2.
**Design**
1. Add a variable "_doc_value_mode" into Class "EsScrollParser" to =indicate whether the data processed by this parser is doc_value_mode or not.
2. "_doc_value_mode" is passed from ESScollReader <- ESScanner <- ScrollQueryBuilder::build() that determines whether DSL is enable doc_value_mode
3. When hits.hits of response from ES is empty and total > 0. We know there are data lines, but the corresponding fields do not exist. EsScrollParser will use "_doc_value_mode" and _total to construct _total lines which fields are assigned with 'NULL'
This PR is just a transitional way，but it is better to move the predicates transformation from Doris BE to Doris BE, in this way, Doris BE is responsible for fetching data from ES.
Add a `enable_keyword_sniff ` configuration item in creating External Elasticsearch Table ，it default to true , would to sniff the `keyword` type on the `text analyzed` Field and return the `json_path` which substitute the origin col name.
```
CREATE EXTERNAL TABLE `test` (
`k1` varchar(20) COMMENT "",
`create_time` datetime COMMENT ""
) ENGINE=ELASTICSEARCH
PROPERTIES (
"hosts" = "http://10.74.167.16:8200",
"user" = "root",
"password" = "root",
"index" = "test",
"type" = "doc",
"enable_keyword_sniff" = "true"
);
```
note: `enable_keyword_sniff` default to "true"
run this SQL：
```
select * from test where k1 = "wu yun feng"
```
Output predicate DSL：
```
{"term":{"k1.keyword":"wu yun feng"}}
```
and in this PR, I remove the elasticsearch version detected logic for now this is useless, maybe future is needed.
Relate Issue: https://github.com/apache/incubator-doris/issues/3248
SQL:
```
select * from test where (k2 = 6 and k3 = 1) or (k2 = 2 and k3 =3 and k4 = 'beijing');
```
Output filter:
```
((#k2:[6 TO 6] #k3:[1 TO 1]) (#(#k2:[2 TO 2] #k3:[3 TO 3]) #k4:beijing))~1
```
SQL:
```
select * from test where (k2 = 6 or k3 = 7) or (k2 = 2 and k3 =3 and (k4 = 'beijing' or k4 = 'zhaochun'));
```
Output filter:
```
(k2:[6 TO 6] k3:[7 TO 7] (#(#k2:[2 TO 2] #k3:[3 TO 3]) #((k4:beijing k4:zhaochun)~1)))~1
```
SQL:
```
select * from test where (k2 = 6 or k3 = 7) or (k2 = 2 and abs(k3) =3 and (k4 = 'beijing' or k4 = 'zhaochun'));
```
Output filter (`abs` can not be pushed down to es, so doris on es would not process this scenario ):
```
match_all
```
Pure DocValue optimization for doris-on-es
Future todo:
Today, for every tuple scan we check if pure_docvalue is enabled, this is not reasonable, should check pure_docvalue enabled for one whole scan outside, I will add this todo in future
* Change label of broker load txn
1. put broker load label into txn label
2. fix the bug of `label is already used`
3. fix partition error of new broker load
* Fix count error in mini load and broker load
There are three params (num_rows_load_total, num_rows_load_filtered, num_rows_load_unselected) which are used to count dpp.norm.ALL and dpp.abnorm.ALL.
num_rows_load_total is the number rows of source file.
num_rows_load_unselected is the not satisfied (where conjuncts) rows of num_rows_load_total
num_rows_load_filtered is the rows (quality not good enough) of (num_rows_load_total-num_rows_load_unselected)
