Fix data loading (#4862)

* Fix loading text data.
* Fix config regex.
* Try to explain the error better in exception.
* Update doc.

doc/contrib/docs.rst

@@ -28,5 +28,3 @@ Examples
 * We are super excited to hear about your story, if you have blogposts,
   tutorials code solutions using XGBoost, please tell us and we will add
   a link in the example pages.
-
-

doc/python/python_intro.rst

@@ -18,6 +18,8 @@ To verify your installation, run the following in Python:
 
   import xgboost as xgb
 
+.. _python_data_interface:
+
 Data Interface
 --------------
 The XGBoost python module is able to load data from:
@@ -50,7 +52,7 @@ The data is stored in a :py:class:`DMatrix <xgboost.DMatrix>` object.
 
   .. note:: Categorical features not supported
 
-    Note that XGBoost does not support categorical features; if your data contains
+    Note that XGBoost does not provide specialization for categorical features; if your data contains
     categorical features, load it as a NumPy array first and then perform
     `one-hot encoding <http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html>`_.
 

doc/tutorials/input_format.rst

@@ -7,6 +7,9 @@ Basic Input Format
 ******************
 XGBoost currently supports two text formats for ingesting data: LibSVM and CSV. The rest of this document will describe the LibSVM format. (See `this Wikipedia article <https://en.wikipedia.org/wiki/Comma-separated_values>`_ for a description of the CSV format.)
 
+.. note::
+   * XGBoost does **not** understand file extensions nor try to guess the file format.  Instead it employs uri format for specifying input file type.  For example if you provide a `csv` file ``./data.train.csv`` as input, XGBoost will use the default libsvm parser to digest it and generate a parser error.  Instead, users need to provide an uri in the form of ``train.csv?format=csv``.  For external memory input, the uri should of a form similar to ``train.csv?format=csv#dtrain.cache``.  See :ref:`python_data_interface` also.
+
 For training or predicting, XGBoost takes an instance file with the format as below:
 
 .. code-block:: none

src/common/config.h

@@ -34,8 +34,8 @@ class ConfigParser {
       line_comment_regex_("^#"),
       key_regex_(R"rx(^([^#"'=\r\n\t ]+)[\t ]*=)rx"),
       key_regex_escaped_(R"rx(^(["'])([^"'=\r\n]+)\1[\t ]*=)rx"),
-      value_regex_(R"rx(^([^#"'=\r\n\t ]+)[\t ]*(?:#.*){0,1}$)rx"),
-      value_regex_escaped_(R"rx(^(["'])([^"'=\r\n]+)\1[\t ]*(?:#.*){0,1}$)rx")
+      value_regex_(R"rx(^([^#"'\r\n\t ]+)[\t ]*(?:#.*){0,1}$)rx"),
+      value_regex_escaped_(R"rx(^(["'])([^"'\r\n]+)\1[\t ]*(?:#.*){0,1}$)rx")
   {}
 
   std::string LoadConfigFile(const std::string& path) {

src/data/data.cc

@@ -222,7 +222,35 @@ DMatrix* DMatrix::Load(const std::string& uri,
 
   std::unique_ptr<dmlc::Parser<uint32_t> > parser(
       dmlc::Parser<uint32_t>::Create(fname.c_str(), partid, npart, file_format.c_str()));
-  DMatrix* dmat = DMatrix::Create(parser.get(), cache_file, page_size);
+  DMatrix* dmat;
+
+  try {
+    dmat = DMatrix::Create(parser.get(), cache_file, page_size);
+  } catch (dmlc::Error& e) {
+    std::vector<std::string> splited = common::Split(fname, '#');
+    std::vector<std::string> args = common::Split(splited.front(), '?');
+    std::string format {file_format};
+    if (args.size() == 1 && file_format == "auto") {
+      auto extension = common::Split(args.front(), '.').back();
+      if (extension == "csv" || extension == "libsvm") {
+        format = extension;
+      }
+      if (format == extension) {
+        LOG(WARNING)
+            << "No format parameter is provided in input uri, but found file extension: "
+            << format << " .  "
+            << "Consider providing a uri parameter: filename?format=" << format;
+      } else {
+        LOG(WARNING)
+            << "No format parameter is provided in input uri.  "
+            << "Choosing default parser in dmlc-core.  "
+            << "Consider providing a uri parameter like: filename?format=csv";
+      }
+
+      LOG(FATAL) << "Encountered parser error:\n" << e.what();
+    }
+  }
+
   if (!silent) {
     LOG(CONSOLE) << dmat->Info().num_row_ << 'x' << dmat->Info().num_col_ << " matrix with "
                  << dmat->Info().num_nonzero_ << " entries loaded from " << uri;

tests/cli/machine.conf.in

@@ -9,5 +9,5 @@ max_depth = 3
 
 num_round = 2
 save_period = 0
-data = "@PROJECT_SOURCE_DIR@/demo/data/agaricus.txt.train"
-eval[test] = "@PROJECT_SOURCE_DIR@/demo/data/agaricus.txt.test"
+data = "@PROJECT_SOURCE_DIR@/demo/data/agaricus.txt.train?format=libsvm"
+eval[test] = "@PROJECT_SOURCE_DIR@/demo/data/agaricus.txt.test?format=libsvm"

tests/cpp/data/test_data.cc

@@ -1,5 +1,7 @@
 #include <gtest/gtest.h>
 #include <dmlc/filesystem.h>
+#include <fstream>
+#include <memory>
 #include <vector>
 
 #include "xgboost/data.h"
@@ -81,4 +83,44 @@ TEST(SparsePage, PushCSCAfterTranspose) {
     }
   }
 }
+
+TEST(DMatrix, Uri) {
+  size_t constexpr kRows {16};
+  size_t constexpr kCols {8};
+  std::vector<float> data (kRows * kCols);
+
+  for (size_t i = 0; i < kRows * kCols; ++i) {
+    data[i] = i;
+  }
+
+  dmlc::TemporaryDirectory tmpdir;
+  std::string path = tmpdir.path + "/small.csv";
+
+  std::ofstream fout(path);
+  ASSERT_TRUE(fout);
+  size_t i = 0;
+  for (size_t r = 0; r < kRows; ++r) {
+    for (size_t c = 0; c < kCols; ++c) {
+      fout << data[i];
+      i++;
+      if (c != kCols - 1) {
+        fout << ",";
+      }
+    }
+    fout << "\n";
+  }
+  fout.flush();
+  fout.close();
+
+  std::unique_ptr<DMatrix> dmat;
+  // FIXME(trivialfis): Enable the following test by restricting csv parser in dmlc-core.
+  // EXPECT_THROW(dmat.reset(DMatrix::Load(path, false, true)), dmlc::Error);
+
+  std::string uri = path + "?format=csv";
+  dmat.reset(DMatrix::Load(uri, false, true));
+
+  ASSERT_EQ(dmat->Info().num_col_, kCols);
+  ASSERT_EQ(dmat->Info().num_row_, kRows);
+}
+
 }  // namespace xgboost