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1.微服务谐波模块因influxDB数据库改正，更改部分sql语句

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2.提交公共的字段、表到公共类中
This commit is contained in:
njcn_dhj
2022-06-29 11:39:25 +08:00
parent 90af2c3693
commit 246ef1c15e
3 changed files with 33 additions and 22 deletions
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36
pqs-harmonic/harmonic-boot/src/main/java/com/njcn/harmonic/service/impl/HarmInHarmServiceImpl.java
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@@ -74,25 +74,25 @@ public class HarmInHarmServiceImpl implements HarmInHarmService {
stringBuilder.append(" and ").append(Param.VALUETYPE + "='").append("CP95").append("'");
String sql = "";
if (harmState == 0) {
sql = "SELECT MEAN(V_2) as V2, MEAN(V_3) as V3, MEAN(V_4) as V4, MEAN(V_5) as V5, MEAN(V_6) as V6, MEAN(V_7) as V7," +
" MEAN(V_8) as V8, MEAN(V_9) as V9, MEAN(V_10) as V10, MEAN(V_11) as V11, MEAN(V_12) as V12, MEAN(V_13) as V13," +
" MEAN(V_14) as V14, MEAN(V_15) as V15, MEAN(V_16) as V16, MEAN(V_17) as V17, MEAN(V_18) as V18," +
" MEAN(V_19) as V19, MEAN(V_20) as V20, MEAN(V_21) as V21," +
" MEAN(V_22) as V22, MEAN(V_23) as V23, MEAN(V_24) as V24, MEAN(V_25) as V25, MEAN(V_26) as V25, MEAN(V_27) as V27, MEAN(V_28) as V28," +
" MEAN(V_29) as V29, MEAN(V_30) as V30, MEAN(V_31) as V31, MEAN(V_32) as V32, MEAN(V_33) as V33, MEAN(V_34) as V34, MEAN(V_35) as V35," +
" MEAN(V_36) as V36, MEAN(V_37) as V37, MEAN(V_38) as V38, MEAN(V_39) as V39, MEAN(V_40) as V40, MEAN(V_41) as V41, MEAN(V_42) as V42," +
" MEAN(V_43) as V43, MEAN(V_44) as V44, MEAN(V_45) as V45, MEAN(V_46) as V46, MEAN(V_47) as V47, MEAN(V_48) as V48, MEAN(V_49) as V49," +
" MEAN(V_50) as V50 FROM Data_HarmRate_V WHERE " + stringBuilder.toString() + " and phasic_type !='T' order by time asc;";
sql = "SELECT MEAN(v_2) as V2, MEAN(v_3) as V3, MEAN(v_4) as V4, MEAN(v_5) as V5, MEAN(v_6) as V6, MEAN(v_7) as V7," +
" MEAN(v_8) as V8, MEAN(v_9) as V9, MEAN(v_10) as V10, MEAN(v_11) as V11, MEAN(v_12) as V12, MEAN(v_13) as V13," +
" MEAN(v_14) as V14, MEAN(v_15) as V15, MEAN(v_16) as V16, MEAN(v_17) as V17, MEAN(v_18) as V18," +
" MEAN(v_19) as V19, MEAN(v_20) as V20, MEAN(v_21) as V21," +
" MEAN(v_22) as V22, MEAN(v_23) as V23, MEAN(v_24) as V24, MEAN(v_25) as V25, MEAN(v_26) as V25, MEAN(v_27) as V27, MEAN(v_28) as V28," +
" MEAN(v_29) as V29, MEAN(v_30) as V30, MEAN(v_31) as V31, MEAN(v_32) as V32, MEAN(v_33) as V33, MEAN(v_34) as V34, MEAN(v_35) as V35," +
" MEAN(v_36) as V36, MEAN(v_37) as V37, MEAN(v_38) as V38, MEAN(v_39) as V39, MEAN(v_40) as V40, MEAN(v_41) as V41, MEAN(v_42) as V42," +
" MEAN(v_43) as V43, MEAN(v_44) as V44, MEAN(v_45) as V45, MEAN(v_46) as V46, MEAN(v_47) as V47, MEAN(v_48) as V48, MEAN(v_49) as V49," +
" MEAN(v_50) as V50 FROM data_harmrate_v WHERE " + stringBuilder.toString() + " and phasic_type !='T' order by time asc tz('Asia/Shanghai');";
} else {
sql = "SELECT MEAN(I_2) as I2, MEAN(I_3) as I3, MEAN(I_4) as I4, MEAN(I_5) as I5, MEAN(I_6) as I6, MEAN(I_7) as I7," +
" MEAN(I_8) as I8, MEAN(I_9) as I9, MEAN(I_10) as I10, MEAN(I_11) as I11, MEAN(I_12) as I12, MEAN(I_13) as I13," +
" MEAN(I_14) as I14, MEAN(I_15) as I15, MEAN(I_16) as I16, MEAN(I_17) as I17, MEAN(I_18) as I18," +
" MEAN(I_19) as I19, MEAN(I_20) as I20, MEAN(I_21) as I21," +
" MEAN(I_22) as I22, MEAN(I_23) as I23, MEAN(I_24) as I24, MEAN(I_25) as I25, MEAN(I_26) as I25, MEAN(I_27) as I27, MEAN(I_28) as I28," +
" MEAN(I_29) as I29, MEAN(I_30) as I30, MEAN(I_31) as I31, MEAN(I_32) as I32, MEAN(I_33) as I33, MEAN(I_34) as I34, MEAN(I_35) as I35," +
" MEAN(I_36) as I36, MEAN(I_37) as I37, MEAN(I_38) as I38, MEAN(I_39) as I39, MEAN(I_40) as I40, MEAN(I_41) as I41, MEAN(I_42) as I42," +
" MEAN(I_43) as I43, MEAN(I_44) as I44, MEAN(I_45) as I45, MEAN(I_46) as I46, MEAN(I_47) as I47, MEAN(I_48) as I48, MEAN(I_49) as I49," +
" MEAN(I_50) as I50 FROM Data_I WHERE " + stringBuilder.toString() + " and phasic_type !='T' order by time asc;";
sql = "SELECT MEAN(i_2) as I2, MEAN(i_3) as I3, MEAN(i_4) as I4, MEAN(i_5) as I5, MEAN(i_6) as I6, MEAN(i_7) as I7," +
" MEAN(i_8) as I8, MEAN(i_9) as I9, MEAN(i_10) as I10, MEAN(i_11) as I11, MEAN(i_12) as I12, MEAN(i_13) as I13," +
" MEAN(i_14) as I14, MEAN(i_15) as I15, MEAN(i_16) as I16, MEAN(i_17) as I17, MEAN(i_18) as I18," +
" MEAN(i_19) as I19, MEAN(i_20) as I20, MEAN(i_21) as I21," +
" MEAN(i_22) as I22, MEAN(i_23) as I23, MEAN(i_24) as I24, MEAN(i_25) as I25, MEAN(i_26) as I25, MEAN(i_27) as I27, MEAN(i_28) as I28," +
" MEAN(i_29) as I29, MEAN(i_30) as I30, MEAN(i_31) as I31, MEAN(i_32) as I32, MEAN(i_33) as I33, MEAN(i_34) as I34, MEAN(i_35) as I35," +
" MEAN(i_36) as I36, MEAN(i_37) as I37, MEAN(i_38) as I38, MEAN(i_39) as I39, MEAN(i_40) as I40, MEAN(i_41) as I41, MEAN(i_42) as I42," +
" MEAN(i_43) as I43, MEAN(i_44) as I44, MEAN(i_45) as I45, MEAN(i_46) as I46, MEAN(i_47) as I47, MEAN(i_48) as I48, MEAN(i_49) as I49," +
" MEAN(i_50) as I50 FROM data_i WHERE " + stringBuilder.toString() + " and phasic_type !='T' order by time asc tz('Asia/Shanghai');";
}
queryResult = influxDbUtils.query(sql);
if (queryResult.getResults().get(0).getSeries() != null) {