Orientdb Slow import large dataset how to make it faster? - performance

Question

I'm working on a network of 17M edges and 20K vrtices , and I'm loading it into Orientdb using ETL tool but it is taking forever to load.
I tried the batch varying from 1000 to 100000 , yet still no change .
Is there an optimized way to make it load faster ? other tha using Java API
Any help would be appreciated.
I'm using 2.2.20 community version .
Here is the ETL fo import :
{
"source": { "file": { "path": "C:/Users/Muuna/Desktop/files/H.csv" } },
"extractor": { "csv": {
"separator": ",",
"columnsOnFirstLine": true,
"ignoreEmptyLines": true,
"columns": ["id:Integer","p1:String","p2:String","s:Integer"] } },
"transformers": [
{ "command": { "command": "UPDATE H set p='${input.p1}' UPSERT WHERE p='${input.p1}'"},"vertex": { "class": "H", "skipDuplicates": true} }
],
"loader": {
"orientdb": {
"dbURL": "PLOCAL:C:/orientdb/databases/Graph",
"dbUser": "admin",
"dbPassword": "admin",
"dbType": "graph",
"classes": [
{"name": "H", "extends": "V"},
{"name": "HAS_S", "extends": "E"}
],"indexes": [ {"class":"H", "fields":["p:String"], "type":"UNIQUE" }]
}
}
}
Based on [1]: orientdb load graph csv of nodes and edges
The same script is loaded twice to import the 2 vertices and another ETL for loading the edges .
Edges .
Based on [Ref][1]
{
"source": { "file": { "path": "C:/Users/Muuna/Desktop/files/H.csv" } },
"extractor": { "csv": {
"separator": ",",
"columnsOnFirstLine": true,
"ignoreEmptyLines": true,
"columns": ["id:Integer","p1:String","p2:String","s:Integer"] } },
"transformers": [
{ "command": { "command": "CREATE EDGE HAS_S FROM (SELECT FROM H WHERE p='${input.p1}') TO (SELECT FROM H WHERE p='${input.p2}') set score=${input.s}"} }
],
"loader": {
"orientdb": {
"dbURL": "PLOCAL:C:/orientdb/databases/Graph",
"dbUser": "admin",
"dbPassword": "admin",
"dbType": "graph",
"classes": [
{"name": "H", "extends": "V"},
{"name": "HAS_S", "extends": "E"}
],"indexes": [ {"class":"H", "fields":["p:String"], "type":"UNIQUE" }]
}
}
}