Merge branch 'branch-21.10' into fea-backref-bracket-syntax

conda/environments/cudf_dev_cuda11.0.yml

@@ -40,8 +40,8 @@ dependencies:
   - mypy=0.782
   - typing_extensions
   - pre_commit
-  - dask>=2021.6.0
-  - distributed>=2021.6.0
+  - dask>=2021.6.0,<=2021.07.1
+  - distributed>=2021.6.0,<=2021.07.1
   - streamz
   - arrow-cpp=4.0.1
   - dlpack>=0.5,<0.6.0a0

conda/environments/cudf_dev_cuda11.2.yml

@@ -40,8 +40,8 @@ dependencies:
   - mypy=0.782
   - typing_extensions
   - pre_commit
-  - dask>=2021.6.0
-  - distributed>=2021.6.0
+  - dask>=2021.6.0,<=2021.07.1
+  - distributed>=2021.6.0,<=2021.07.1
   - streamz
   - arrow-cpp=4.0.1
   - dlpack>=0.5,<0.6.0a0

conda/recipes/custreamz/meta.yaml

@@ -31,8 +31,8 @@ requirements:
     - python
     - streamz 
     - cudf {{ version }}
-    - dask>=2021.6.0
-    - distributed>=2021.6.0
+    - dask>=2021.6.0,<=2021.07.1
+    - distributed>=2021.6.0,<=2021.07.1
     - python-confluent-kafka
     - cudf_kafka {{ version }}
 

conda/recipes/dask-cudf/meta.yaml

@@ -26,13 +26,13 @@ requirements:
   host:
     - python
     - cudf {{ version }}
-    - dask>=2021.6.0
-    - distributed>=2021.6.0
+    - dask>=2021.6.0,<=2021.07.1
+    - distributed>=2021.6.0,<=2021.07.1
   run:
     - python
     - cudf {{ version }}
-    - dask>=2021.6.0
-    - distributed>=2021.6.0
+    - dask>=2021.6.0,<=2021.07.1
+    - distributed>=2021.6.0,<=2021.07.1
 
 test:
   requires:

cpp/src/io/orc/writer_impl.cu

@@ -575,8 +575,8 @@ orc_streams writer::impl::create_streams(host_span<orc_column_view> columns,
         break;
       }
       case TypeKind::TIMESTAMP:
-        add_RLE_stream(gpu::CI_DATA, DATA, TypeKind::INT);
-        add_RLE_stream(gpu::CI_DATA2, SECONDARY, TypeKind::INT);
+        add_RLE_stream(gpu::CI_DATA, DATA, TypeKind::LONG);
+        add_RLE_stream(gpu::CI_DATA2, SECONDARY, TypeKind::LONG);
         column.set_orc_encoding(DIRECT_V2);
         break;
       case TypeKind::DECIMAL:

java/README.md

@@ -35,8 +35,8 @@ most modern cuda drivers.
 ```
 
 In some cases there may be a classifier to indicate the version of cuda required. See the 
-Build From Source section below for more information about when this can happen. No official
-release of the jar will have a classifier on it.
+[Build From Source](#build-from-source) section below for more information about when this
+can happen. No official release of the jar will have a classifier on it.
 
 CUDA 11.0:
 ```xml
@@ -51,9 +51,9 @@ CUDA 11.0:
 ## Build From Source
 
 Build [libcudf](../cpp) first, and make sure the JDK is installed and available. Specify
-the cmake option `-DCUDF_USE_ARROW_STATIC=ON` when building so that Apache Arrow is linked
-statically to libcudf, as this will help create a jar that does not require Arrow and its
-dependencies to be available in the runtime environment.
+the cmake option `-DCUDF_USE_ARROW_STATIC=ON -DCUDF_ENABLE_ARROW_S3=OFF` when building so
+that Apache Arrow is linked statically to libcudf, as this will help create a jar that
+does not require Arrow and its dependencies to be available in the runtime environment.
 
 After building libcudf, the Java bindings can be built via Maven, e.g.:
 ```
@@ -63,6 +63,18 @@ mvn clean install
 If you have a compatible GPU on your build system the tests will use it.  If not you will see a
 lot of skipped tests.
 
+### Using the Java CI Docker Image
+
+If you are interested in building a Java cudf jar that is similar to the official releases
+that can run on all modern Linux systems, see the [Java CI README](ci/README.md) for
+instructions on how to build within a Docker environment using devtoolset. Note that
+building the jar without the Docker setup and script will likely produce a jar that can
+only run in environments similar to that of the build machine.
+
+If you decide to build without Docker and the build script, examining the cmake and Maven
+settings in the [Java CI build script](ci/build-in-docker.sh) can be helpful if you are
+encountering difficulties during the build.
+
 ## Dynamically Linking Arrow
 
 Since libcudf builds by default with a dynamically linked Arrow dependency, it may be

java/src/main/java/ai/rapids/cudf/ColumnView.java

@@ -2465,6 +2465,48 @@ public final ColumnVector stringReplace(Scalar target, Scalar replace) {
         replace.getScalarHandle()));
   }
 
+  /**
+   * For each string, replaces any character sequence matching the given pattern using the
+   * replacement string scalar.
+   *
+   * @param pattern The regular expression pattern to search within each string.
+   * @param repl The string scalar to replace for each pattern match.
+   * @return A new column vector containing the string results.
+   */
+  public final ColumnVector replaceRegex(String pattern, Scalar repl) {
+    return replaceRegex(pattern, repl, -1);
+  }
+
+  /**
+   * For each string, replaces any character sequence matching the given pattern using the
+   * replacement string scalar.
+   *
+   * @param pattern The regular expression pattern to search within each string.
+   * @param repl The string scalar to replace for each pattern match.
+   * @param maxRepl The maximum number of times a replacement should occur within each string.
+   * @return A new column vector containing the string results.
+   */
+  public final ColumnVector replaceRegex(String pattern, Scalar repl, int maxRepl) {
+    if (!repl.getType().equals(DType.STRING)) {
+      throw new IllegalArgumentException("Replacement must be a string scalar");
+    }
+    return new ColumnVector(replaceRegex(getNativeView(), pattern, repl.getScalarHandle(),
+        maxRepl));
+  }
+
+  /**
+   * For each string, replaces any character sequence matching any of the regular expression
+   * patterns with the corresponding replacement strings.
+   *
+   * @param patterns The regular expression patterns to search within each string.
+   * @param repls The string scalars to replace for each corresponding pattern match.
+   * @return A new column vector containing the string results.
+   */
+  public final ColumnVector replaceMultiRegex(String[] patterns, ColumnView repls) {
+    return new ColumnVector(replaceMultiRegex(getNativeView(), patterns,
+        repls.getNativeView()));
+  }
+
   /**
    * For each string, replaces any character sequence matching the given pattern
    * using the replace template for back-references.
@@ -3241,6 +3283,28 @@ private static native long substringColumn(long columnView, long startColumn, lo
    */
   private static native long stringReplace(long columnView, long target, long repl) throws CudfException;
 
+  /**
+   * Native method for replacing each regular expression pattern match with the specified
+   * replacement string.
+   * @param columnView native handle of the cudf::column_view being operated on.
+   * @param pattern The regular expression pattern to search within each string.
+   * @param repl native handle of the cudf::scalar containing the replacement string.
+   * @param maxRepl maximum number of times to replace the pattern within a string
+   * @return native handle of the resulting cudf column containing the string results.
+   */
+  private static native long replaceRegex(long columnView, String pattern,
+                                          long repl, long maxRepl) throws CudfException;
+
+  /**
+   * Native method for multiple instance regular expression replacement.
+   * @param columnView native handle of the cudf::column_view being operated on.
+   * @param patterns native handle of the cudf::column_view containing the regex patterns.
+   * @param repls The replacement template for creating the output string.
+   * @return native handle of the resulting cudf column containing the string results.
+   */
+  private static native long replaceMultiRegex(long columnView, String[] patterns,
+                                               long repls) throws CudfException;
+
   /**
    * Native method for replacing any character sequence matching the given pattern
    * using the replace template for back-references.

java/src/main/native/CMakeLists.txt

@@ -293,6 +293,14 @@ target_compile_definitions(cudfjni
 
 if(USE_GDS)
     add_library(cufilejni SHARED "src/CuFileJni.cpp")
+    SET_TARGET_PROPERTIES(cufilejni
+        PROPERTIES BUILD_RPATH "\$ORIGIN"
+                   # set target compile options
+                   CXX_STANDARD                        17
+                   CXX_STANDARD_REQUIRED               ON
+                   CUDA_STANDARD                       17
+                   CUDA_STANDARD_REQUIRED              ON
+    )
     target_include_directories(cufilejni PRIVATE "${cuFile_INCLUDE_DIRS}")
     target_link_libraries(cufilejni PRIVATE cudfjni "${cuFile_LIBRARIES}")
 endif(USE_GDS)

java/src/main/native/src/ColumnViewJni.cpp

@@ -1213,6 +1213,51 @@ JNIEXPORT jlong JNICALL Java_ai_rapids_cudf_ColumnView_mapContains(JNIEnv *env,
   CATCH_STD(env, 0);
 }
 
+JNIEXPORT jlong JNICALL Java_ai_rapids_cudf_ColumnView_replaceRegex(JNIEnv *env, jclass,
+                                                                    jlong j_column_view,
+                                                                    jstring j_pattern, jlong j_repl,
+                                                                    jlong j_maxrepl) {
+
+  JNI_NULL_CHECK(env, j_column_view, "column is null", 0);
+  JNI_NULL_CHECK(env, j_pattern, "pattern string is null", 0);
+  JNI_NULL_CHECK(env, j_repl, "replace scalar is null", 0);
+  try {
+    cudf::jni::auto_set_device(env);
+    auto cv = reinterpret_cast<cudf::column_view const *>(j_column_view);
+    cudf::strings_column_view scv(*cv);
+    cudf::jni::native_jstring pattern(env, j_pattern);
+    auto repl = reinterpret_cast<cudf::string_scalar const *>(j_repl);
+
+    std::unique_ptr<cudf::column> result =
+        cudf::strings::replace_re(scv, pattern.get(), *repl, j_maxrepl);
+    return reinterpret_cast<jlong>(result.release());
+  }
+  CATCH_STD(env, 0);
+}
+
+JNIEXPORT jlong JNICALL Java_ai_rapids_cudf_ColumnView_replaceMultiRegex(JNIEnv *env, jclass,
+                                                                         jlong j_column_view,
+                                                                         jobjectArray j_patterns,
+                                                                         jlong j_repls) {
+
+  JNI_NULL_CHECK(env, j_column_view, "column is null", 0);
+  JNI_NULL_CHECK(env, j_patterns, "patterns is null", 0);
+  JNI_NULL_CHECK(env, j_repls, "repls is null", 0);
+  try {
+    cudf::jni::auto_set_device(env);
+    auto cv = reinterpret_cast<cudf::column_view const *>(j_column_view);
+    cudf::strings_column_view scv(*cv);
+    cudf::jni::native_jstringArray patterns(env, j_patterns);
+    auto repl_cv = reinterpret_cast<cudf::column_view const *>(j_repls);
+    cudf::strings_column_view repl_scv(*repl_cv);
+
+    std::unique_ptr<cudf::column> result =
+        cudf::strings::replace_re(scv, patterns.as_cpp_vector(), repl_scv);
+    return reinterpret_cast<jlong>(result.release());
+  }
+  CATCH_STD(env, 0);
+}
+
 JNIEXPORT jlong JNICALL Java_ai_rapids_cudf_ColumnView_stringReplaceWithBackrefs(
     JNIEnv *env, jclass, jlong column_view, jstring patternObj, jstring replaceObj) {
 

java/src/test/java/ai/rapids/cudf/ColumnVectorTest.java

@@ -4479,6 +4479,46 @@ void teststringReplaceThrowsException() {
     });
   }
 
+  @Test
+  void testReplaceRegex() {
+    try (ColumnVector v =
+             ColumnVector.fromStrings("title and Title with title", "nothing", null, "Title");
+         Scalar repl = Scalar.fromString("Repl");
+         ColumnVector actual = v.replaceRegex("[tT]itle", repl);
+         ColumnVector expected =
+             ColumnVector.fromStrings("Repl and Repl with Repl", "nothing", null, "Repl")) {
+      assertColumnsAreEqual(expected, actual);
+    }
+
+    try (ColumnVector v =
+             ColumnVector.fromStrings("title and Title with title", "nothing", null, "Title");
+         Scalar repl = Scalar.fromString("Repl");
+         ColumnVector actual = v.replaceRegex("[tT]itle", repl, 0)) {
+      assertColumnsAreEqual(v, actual);
+    }
+
+    try (ColumnVector v =
+             ColumnVector.fromStrings("title and Title with title", "nothing", null, "Title");
+         Scalar repl = Scalar.fromString("Repl");
+         ColumnVector actual = v.replaceRegex("[tT]itle", repl, 1);
+         ColumnVector expected =
+             ColumnVector.fromStrings("Repl and Title with title", "nothing", null, "Repl")) {
+      assertColumnsAreEqual(expected, actual);
+    }
+  }
+
+  @Test
+  void testReplaceMultiRegex() {
+    try (ColumnVector v =
+             ColumnVector.fromStrings("title and Title with title", "nothing", null, "Title");
+         ColumnVector repls = ColumnVector.fromStrings("Repl", "**");
+         ColumnVector actual = v.replaceMultiRegex(new String[] { "[tT]itle", "and|th" }, repls);
+         ColumnVector expected =
+             ColumnVector.fromStrings("Repl ** Repl wi** Repl", "no**ing", null, "Repl")) {
+      assertColumnsAreEqual(expected, actual);
+    }
+  }
+
   @Test
   void testStringReplaceWithBackrefs() {
 

python/cudf/cudf/tests/test_orc.py

@@ -1152,3 +1152,22 @@ def test_chunked_orc_writer_lists():
 
     got = pa.orc.ORCFile(buffer).read().to_pandas()
     assert_eq(expect, got)
+
+
+def test_writer_timestamp_stream_size(datadir, tmpdir):
+    pdf_fname = datadir / "TestOrcFile.largeTimestamps.orc"
+    gdf_fname = tmpdir.join("gdf.orc")
+
+    try:
+        orcfile = pa.orc.ORCFile(pdf_fname)
+    except Exception as excpr:
+        if type(excpr).__name__ == "ArrowIOError":
+            pytest.skip(".orc file is not found")
+        else:
+            print(type(excpr).__name__)
+
+    expect = orcfile.read().to_pandas()
+    cudf.from_pandas(expect).to_orc(gdf_fname.strpath)
+    got = pa.orc.ORCFile(gdf_fname).read().to_pandas()
+
+    assert_eq(expect, got)

python/custreamz/dev_requirements.txt

@@ -3,8 +3,8 @@
 flake8==3.8.3
 black==19.10b0
 isort==5.6.4
-dask>=2021.6.0
-distributed>=2021.6.0
+dask>=2021.6.0,<=2021.07.1
+distributed>=2021.6.0,<=2021.07.1
 streamz
 python-confluent-kafka
 pytest

python/dask_cudf/dev_requirements.txt

@@ -1,7 +1,7 @@
 # Copyright (c) 2021, NVIDIA CORPORATION.
 
-dask>=2021.6.0
-distributed>=2021.6.0
+dask>=2021.6.0,<=2021.07.1
+distributed>=2021.6.0,<=2021.07.1
 fsspec>=0.6.0
 numba>=0.53.1
 numpy

python/dask_cudf/setup.py

@@ -10,8 +10,8 @@
 
 install_requires = [
     "cudf",
-    "dask>=2021.6.0",
-    "distributed>=2021.6.0",
+    "dask>=2021.6.0,<=2021.07.1",
+    "distributed>=2021.6.0,<=2021.07.1",
     "fsspec>=0.6.0",
     "numpy",
     "pandas>=1.0,<1.3.0dev0",
@@ -23,8 +23,8 @@
         "pandas>=1.0,<1.3.0dev0",
         "pytest",
         "numba>=0.53.1",
-        "dask>=2021.6.0",
-        "distributed>=2021.6.0",
+        "dask>=2021.6.0,<=2021.07.1",
+        "distributed>=2021.6.0,<=2021.07.1",
     ]
 }