Transform - can I "group by" splitting values in one row?

Mark_Duncan · May 6, 2020, 5:05pm

I'd like to add a dimension (a single field in each document with values, "buy" or "sell") to create 2 values in a single output record/row.

So in Excel, this would look like splitting a value into 2 columns.

Is this possible in a transform? Either as a group by/dimension to create 2 values or can I filter each value I produce, and I produce a buy_metric and sell_metric for each?

Ultimately, I would like the values output in one record. Not using a simple "group by" to make 2 record results.

Thanks
Mark

Luca_Belluccini · May 6, 2020, 5:28pm

Hello @Mark_Duncan

Would it be possible to get an example of the document(s) and the result you wish to get?

Mark_Duncan · May 6, 2020, 5:52pm

I've just taken this document from the discover page...

I'd like to use the field "side" as described so my output could have the following columns, where "last_fill_qty" and "last_fill_px" are existing fields/values in a document. And where I will turn multiple documents for a day into one row to summarise the day.

timestamp(day), side_last_fill_qty, buy_last_fill_qty

I could make these metrics as Scripted fields for the index pattern, but then they just appear as 0s in the transform output...

I would add additional calculated metrics in my transform output, too.

Thanks in advance!
Mark

Blockquote
{
"_index": "blah-user-orders-2020.05.05",
"_type": "_doc",
"_id": "Ncc45HEB7Yw4QDcGDsLb",
"_version": 1,
"_score": null,
"_source": {
"recv_timestamp": "2020-05-05T09:43:25.838916Z",
"last_fill_time": "0001-01-01T00:00:00.000000Z",
"notional": 0,
"side": "sell",
"quantity": 0.0017,
"instrument": "blah",
"limit_or_market": "limit",
"type": "orders",
"last_fill_qty": 0.0017,
"message": "{"recv_timestamp":"2020-05-05T09:43:25.838916Z","exchange":"blah","instrument":"blah","client_oid":"","order_id":"4845450774989824","side":"sell","price":9050.2,"quantity":0.0017,"limit_or_market":"limit","order_type":"0","status":"filled","notional":0,"filled_notional":15.38534,"filled_size":0,"last_fill_px":9050.2,"last_fill_qty":0.0017,"last_fill_time":"0001-01-01T00:00:00.000000Z","margin_trading":2,"exchange_timestamp":"2020-05-05T09:43:25.830000Z","extra_fields":null}",
"client_oid": "",
"last_fill_px": 9050.2,
"filled_notional": 15.38534,
"@timestamp": "2020-05-05T09:43:30.626Z",
"exchange_timestamp": "2020-05-05T09:43:25.830000Z",
"price": 9050.2,
"filled_size": 0,
"extra_fields": null,
"exchange": "blah",
"margin_trading": 2,
"order_type": "0",
"order_id": "4845450774989824",
"status": "filled"
},
"fields": {
"recv_timestamp": [
"2020-05-05T09:43:25.838Z"
],
"last_fill_time": [
"0001-01-01T00:00:00.000Z"
],
"+/- usdt traded test": [
15.385340536004719
],
"@timestamp": [
"2020-05-05T09:43:30.626Z"
],
"exchange_timestamp": [
"2020-05-05T09:43:25.830Z"
],
"USDT_traded": [
15.385340536004719
],
"+/- base traded": [
-0.0017000000225380063
]
},
"highlight": {
"status": [
"@kibana-highlighted-field@filled@/kibana-highlighted-field@"
]
},
"sort": [
1588671805830
]
}

Luca_Belluccini · May 6, 2020, 11:22pm

Hello @Mark_Duncan, thank you for clarifying the question.

Side comment: we're improving date_nano datatype but aggregations cannot have granularity of nanosecond at the moment. This is not necessary in this case.

Demo data

PUT discusstransform
{
  "mappings": {
    "recv_timestamp": {
      "type": "date_nanos"
    },
    "last_fill_time": {
      "type": "date_nanos"
    },
    "exchange_timestamp": {
      "type": "date_nanos"
    }
  }
}

PUT discusstransform/_doc/1
{
  "recv_timestamp": "2020-05-05T09:43:25.838916Z",
  "last_fill_time": "0001-01-01T00:00:00.000000Z",
  "notional": 0,
  "side": "sell",
  "quantity": 0.0017,
  "instrument": "blah",
  "limit_or_market": "limit",
  "type": "orders",
  "last_fill_qty": 0.0017,
  "client_oid": "",
  "last_fill_px": 9050.2,
  "filled_notional": 15.38534,
  "@timestamp": "2020-05-05T09:43:30.626Z",
  "exchange_timestamp": "2020-05-05T09:43:25.830000Z",
  "price": 9050.2,
  "filled_size": 0,
  "extra_fields": null,
  "exchange": "blah",
  "margin_trading": 2,
  "order_type": "0",
  "order_id": "4845450774989824",
  "status": "filled"
}

PUT discusstransform/_doc/2
{
  "recv_timestamp": "2020-05-05T09:43:25.838916Z",
  "last_fill_time": "0001-01-01T00:00:00.000000Z",
  "notional": 0,
  "side": "buy",
  "quantity": 0.0017,
  "instrument": "blah",
  "limit_or_market": "limit",
  "type": "orders",
  "last_fill_qty": 0.0017,
  "client_oid": "",
  "last_fill_px": 9050.2,
  "filled_notional": 15.38534,
  "@timestamp": "2020-05-05T09:43:30.626Z",
  "exchange_timestamp": "2020-05-05T09:43:25.830000Z",
  "price": 9050.2,
  "filled_size": 0,
  "extra_fields": null,
  "exchange": "blah",
  "margin_trading": 2,
  "order_type": "0",
  "order_id": "4845450774989824",
  "status": "filled"
}

I cannot get exactly what is the metric or value you want to extract from last_fill_qty.

The following transform will generate 2 documents, one for the sell and one for the buy side, per day.

POST _transform/_preview
{
  "source": {
    "index": [
      "discusstransform"
    ]
  },
  "dest": {
    "index": "transform_discusstransform"
  },
  "pivot": {
    "group_by": {
      "day": {
        "date_histogram": {
          "field": "recv_timestamp",
          "calendar_interval": "1d"
        }
      },
      "side": {
        "terms": {
          "field": "side.keyword"
        }
      }
    },
    "aggregations": {
      "sum": {
        "sum": {
          "field": "last_fill_qty"
        }
      },
      "avg": {
        "avg": {
          "field": "last_fill_qty"
        }
      },
      "min": {
        "min": {
          "field": "last_fill_qty"
        }
      },
      "max": {
        "max": {
          "field": "last_fill_qty"
        }
      }
    }
  }
}

If you want to obtain one single document, the other option might be to use scripted metrics.

Example: how to obtain the latest value of last_fill_qty for buy and sell, per day, based on the recv_timestamp.

POST _transform/_preview
{
  "source": {
    "index": [
      "discusstransform"
    ]
  },
  "dest": {
    "index": "transform_discusstransform"
  },
  "pivot": {
    "group_by": {
      "day": {
        "date_histogram": {
          "field": "recv_timestamp",
          "calendar_interval": "1d"
        }
      }
    },
    "aggregations": {
      "values": {
        "scripted_metric": {
          "init_script": """
          state.last_fill_qty = ['sell':0,'buy':0];
          state.recv_timestamp_last = ['sell':0,'buy':0];
          """,
          "map_script": """
          def recv_timestamp = doc.recv_timestamp.value.toInstant().toEpochMilli();
          if(doc['side.keyword'].value == 'sell') {
            if(state.recv_timestamp_last.sell < recv_timestamp) {
              state.last_fill_qty.sell = doc.last_fill_qty.value;
              state.recv_timestamp_last.sell = recv_timestamp;
            }
          } else if (doc['side.keyword'].value == 'buy') {
            if(state.recv_timestamp_last.buy < recv_timestamp) {
              state.last_fill_qty.buy = doc.last_fill_qty.value;
              state.recv_timestamp_last.buy = recv_timestamp;
            }
          }
          """,
          "combine_script": "return state;",
          "reduce_script": """
          def last_fill_qty = ['sell':0,'buy':0];
          def recv_timestamp_last = ['sell':0,'buy':0];
          for(s in states) {
              if(s.recv_timestamp_last.sell > recv_timestamp_last.sell) {
                last_fill_qty.sell = s.last_fill_qty.sell;
                recv_timestamp_last.sell = s.recv_timestamp_last.sell;
              }
              if(s.recv_timestamp_last.buy > recv_timestamp_last.buy) {
                last_fill_qty.buy = s.last_fill_qty.buy;
                recv_timestamp_last.buy = s.recv_timestamp_last.buy;
              }
          }
          return ['sell_last_fill_qty': last_fill_qty.sell, 'buy_last_fill_qty': last_fill_qty.buy ]
          """
        }
      }
    }
  }
}

Result:

{
  "preview" : [
    {
      "values" : {
        "sell_last_fill_qty" : 0.0017000000225380063,
        "buy_last_fill_qty" : 0.0017000000225380063
      },
      "day" : 1588636800000
    }
  ],
  "mappings" : {
    "properties" : {
      "day" : {
        "type" : "date"
      }
    }
  }
}

Mark_Duncan · May 7, 2020, 3:42pm

@Luca_Belluccini that is amazing, thank you

I had used Scripted fields for an index pattern before, but not a scripted metric in a transform.

Being really cheeky, would you have another example that you could share for a sum scripted metric? i.e. I will want to sum the day's side:buy documents last_fill_qty field as my metric.

Many thanks,
Mark

Luca_Belluccini · May 7, 2020, 9:22pm

On Elasticsearch 7.7, you will have the possibility to do:

POST _transform/_preview
{
  "source": {
    "index": [
      "discusstransform"
    ]
  },
  "dest": {
    "index": "transform_discusstransform"
  },
  "pivot": {
    "group_by": {
      "day": {
        "date_histogram": {
          "field": "recv_timestamp",
          "calendar_interval": "1d"
        }
      }
    },
    "aggregations": {
      "sell": {
        "filter": {
          "term": {
            "side.keyword": "sell"
          }
        },
        "aggs": {
          "sum": {
            "sum": {
              "field": "last_fill_qty"
            }
          }
        }
      },
      "buy": {
        "filter": {
          "term": {
            "side.keyword": "buy"
          }
        },
        "aggs": {
          "sum": {
            "sum": {
              "field": "last_fill_qty"
            }
          }
        }
      }
    }
  }
}

Until 7.6:

POST _transform/_preview
{
  "source": {
    "index": [
      "discusstransform"
    ]
  },
  "dest": {
    "index": "transform_discusstransform"
  },
  "pivot": {
    "group_by": {
      "day": {
        "date_histogram": {
          "field": "recv_timestamp",
          "calendar_interval": "1d"
        }
      }
    },
    "aggregations": {
      "values": {
        "scripted_metric": {
          "init_script": """
          state.last_fill_qty = ['sell':0,'buy':0];
          """,
          "map_script": """
          if(doc['side.keyword'].value == 'sell') {
            state.last_fill_qty.sell = doc.last_fill_qty.value;
          } else if (doc['side.keyword'].value == 'buy') {
            state.last_fill_qty.buy = doc.last_fill_qty.value;
          }
          """,
          "combine_script": "return state;",
          "reduce_script": """
          def last_fill_qty = ['sell':0,'buy':0];
          for(s in states) {
            last_fill_qty.sell = s.last_fill_qty.sell;
            last_fill_qty.buy = s.last_fill_qty.buy;
          }
          return ['sell_last_fill_qty': last_fill_qty.sell, 'buy_last_fill_qty': last_fill_qty.buy ]
          """
        }
      }
    }
  }
}

Mark_Duncan · May 11, 2020, 2:25pm

Hey @Luca_Belluccini roll on v7.7

Thanks again for your help here. I've tried implementing your "Until 7.6" code, but it does appear to only return a single value - the equivalent of a top hit of the final record. I get the same result as your previous reply.

However, I was hoping to get a sum of all "last_fill_qty" values from multiple documents for that day. Could you advise on the change needed, please?

Luca_Belluccini · May 11, 2020, 5:56pm

Closer than you might think.

It doesn't work because I forgot to ... add the values!
Also force 0.0 or the sum will be done on integers.

POST _transform/_preview
{
  "source": {
    "index": [
      "discusstransform"
    ]
  },
  "dest": {
    "index": "transform_discusstransform"
  },
  "pivot": {
    "group_by": {
      "day": {
        "date_histogram": {
          "field": "recv_timestamp",
          "calendar_interval": "1d"
        }
      }
    },
    "aggregations": {
      "values": {
        "scripted_metric": {
          "init_script": """
          state.last_fill_qty = ['sell':0.0,'buy':0.0];
          """,
          "map_script": """
          if(doc['side.keyword'].value == 'sell') {
            state.last_fill_qty.sell += doc.last_fill_qty.value;
          } else if (doc['side.keyword'].value == 'buy') {
            state.last_fill_qty.buy += doc.last_fill_qty.value;
          }
          """,
          "combine_script": "return state;",
          "reduce_script": """
          def last_fill_qty = ['sell':0.0,'buy':0.0];
          for(s in states) {
            last_fill_qty.sell += s.last_fill_qty.sell;
            last_fill_qty.buy += s.last_fill_qty.buy;
          }
          return ['sell_last_fill_qty': last_fill_qty.sell, 'buy_last_fill_qty': last_fill_qty.buy ]
          """
        }
      }
    }
  }
}

Mark_Duncan · May 14, 2020, 12:26pm

I see it's been released

Thanks so much for your help mate

system · June 11, 2020, 12:26pm

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Transform - can I "group by" splitting values in one row?

Demo data

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