[docs] Change some 'parallel learning' references to 'distributed learning' (#4000)

* [docs] Change some 'parallel learning' references to 'distributed learning'

* found a few more

* one more reference

src/io/config.cpp

@@ -374,7 +374,7 @@ void Config::CheckParamConflict() {
   }
   if (is_parallel && (monotone_constraints_method == std::string("intermediate") || monotone_constraints_method == std::string("advanced"))) {
     // In distributed mode, local node doesn't have histograms on all features, cannot perform "intermediate" monotone constraints.
-    Log::Warning("Cannot use \"intermediate\" or \"advanced\" monotone constraints in parallel learning, auto set to \"basic\" method.");
+    Log::Warning("Cannot use \"intermediate\" or \"advanced\" monotone constraints in distributed learning, auto set to \"basic\" method.");
     monotone_constraints_method = "basic";
   }
   if (feature_fraction_bynode != 1.0 && (monotone_constraints_method == std::string("intermediate") || monotone_constraints_method == std::string("advanced"))) {

src/io/dataset_loader.cpp

@@ -180,10 +180,10 @@ void CheckSampleSize(size_t sample_cnt, size_t num_data) {
 }
 
 Dataset* DatasetLoader::LoadFromFile(const char* filename, int rank, int num_machines) {
-  // don't support query id in data file when training in parallel
+  // don't support query id in data file when using distributed training
   if (num_machines > 1 && !config_.pre_partition) {
     if (group_idx_ > 0) {
-      Log::Fatal("Using a query id without pre-partitioning the data file is not supported for parallel training.\n"
+      Log::Fatal("Using a query id without pre-partitioning the data file is not supported for distributed training.\n"
                  "Please use an additional query file or pre-partition the data");
     }
   }

src/io/metadata.cpp

@@ -22,7 +22,7 @@ Metadata::Metadata() {
 
 void Metadata::Init(const char* data_filename) {
   data_filename_ = data_filename;
-  // for lambdarank, it needs query data for partition data in parallel learning
+  // for lambdarank, it needs query data for partition data in distributed learning
   LoadQueryBoundaries();
   LoadWeights();
   LoadQueryWeights();
@@ -187,7 +187,7 @@ void Metadata::CheckOrPartition(data_size_t num_all_data, const std::vector<data
     }
   } else {
     if (!queries_.empty()) {
-      Log::Fatal("Cannot used query_id for parallel training");
+      Log::Fatal("Cannot used query_id for distributed training");
     }
     data_size_t num_used_data = static_cast<data_size_t>(used_data_indices.size());
     // check weights