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@@ -1,5 +1,6 @@
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package com.tzld.piaoquan.ad.engine.service.predict.model.threshold;
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+import com.alibaba.fastjson.JSONObject;
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import com.tzld.piaoquan.ad.engine.commons.util.JSONUtils;
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import com.tzld.piaoquan.ad.engine.service.predict.container.RandWContainer;
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import com.tzld.piaoquan.ad.engine.service.predict.param.ThresholdPredictModelParam;
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@@ -65,8 +66,20 @@ public class RandomPredict673Model extends ThresholdPredictModel {
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result.put("threshold", threshold);
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result.put("model", this.initName());
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- log.info("广告跳出选择 -- 673实验结果: {}, 参数: {}, {}, {}, {}",
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- JSONUtils.toJson(result), appType, modelParam.getMid(), abParamKey, thresholdParamKey);
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+ JSONObject logJson = new JSONObject();
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+ logJson.putAll(result);
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+ logJson.put("mid", modelParam.getMid());
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+ logJson.put("appType", appType);
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+ logJson.put("expId", "673");
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+ logJson.put("userExternalSource", modelParam.getUserExternalSource());
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+ logJson.put("shareType", modelParam.getUserExtraFuture("shareType").toString());
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+ logJson.put("shareLayer", modelParam.getShareLayer());
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+ logJson.put("thresholdParamKey", thresholdParamKey);
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+ logJson.put("adPlatformType", modelParam.getAdPlatformType());
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+
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+ log.info("广告跳出选择 -- 673实验结果: {}, 参数: {}",
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+ JSONUtils.toJson(result), logJson.toJSONString());
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+
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return result;
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}
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