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Posted to commits@hivemall.apache.org by my...@apache.org on 2017/02/07 09:16:00 UTC
incubator-hivemall git commit: Close #38: Fixed drop function DDLs
Repository: incubator-hivemall
Updated Branches:
refs/heads/master 52f05f43d -> 231f4e055
Close #38: Fixed drop function DDLs
Project: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/commit/231f4e05
Tree: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/tree/231f4e05
Diff: http://git-wip-us.apache.org/repos/asf/incubator-hivemall/diff/231f4e05
Branch: refs/heads/master
Commit: 231f4e0551552cc6e70f0d96db12847e02ad1aca
Parents: 52f05f4
Author: Yuming Wang <wg...@gmail.com>
Authored: Tue Feb 7 18:15:28 2017 +0900
Committer: myui <yu...@gmail.com>
Committed: Tue Feb 7 18:15:28 2017 +0900
----------------------------------------------------------------------
resources/ddl/define-additional.hive | 12 +-
resources/ddl/define-all.deprecated.hive | 56 ++---
resources/ddl/define-all.hive | 322 +++++++++++++-------------
3 files changed, 195 insertions(+), 195 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/231f4e05/resources/ddl/define-additional.hive
----------------------------------------------------------------------
diff --git a/resources/ddl/define-additional.hive b/resources/ddl/define-additional.hive
index 890edad..7bbfcf4 100644
--- a/resources/ddl/define-additional.hive
+++ b/resources/ddl/define-additional.hive
@@ -6,24 +6,24 @@
-- NLP features --
------------------
-drop temporary function tokenize_ja;
+drop temporary function if exists tokenize_ja;
create temporary function tokenize_ja as 'hivemall.nlp.tokenizer.KuromojiUDF';
------------------------------
-- XGBoost related features --
------------------------------
-drop temporary function train_xgboost_regr;
+drop temporary function if exists train_xgboost_regr;
create temporary function train_xgboost_regr as 'hivemall.xgboost.regression.XGBoostRegressionUDTF';
-drop temporary function train_xgboost_classifier;
+drop temporary function if exists train_xgboost_classifier;
create temporary function train_xgboost_classifier as 'hivemall.xgboost.classification.XGBoostBinaryClassifierUDTF';
-drop temporary function train_multiclass_xgboost_classifier;
+drop temporary function if exists train_multiclass_xgboost_classifier;
create temporary function train_multiclass_xgboost_classifier as 'hivemall.xgboost.classification.XGBoostMulticlassClassifierUDTF';
-drop temporary function xgboost_predict;
+drop temporary function if exists xgboost_predict;
create temporary function xgboost_predict as 'hivemall.xgboost.tools.XGBoostPredictUDTF';
-drop temporary function xgboost_multiclass_predict;
+drop temporary function if exists xgboost_multiclass_predict;
create temporary function xgboost_multiclass_predict as 'hivemall.xgboost.tools.XGBoostMulticlassPredictUDTF';
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/231f4e05/resources/ddl/define-all.deprecated.hive
----------------------------------------------------------------------
diff --git a/resources/ddl/define-all.deprecated.hive b/resources/ddl/define-all.deprecated.hive
index 58e027f..001666b 100644
--- a/resources/ddl/define-all.deprecated.hive
+++ b/resources/ddl/define-all.deprecated.hive
@@ -1,83 +1,83 @@
-drop temporary function perceptron;
+drop temporary function if exists perceptron;
create temporary function perceptron as 'hivemall.classifier.PerceptronUDTF';
-drop temporary function adagrad_rda;
+drop temporary function if exists adagrad_rda;
create temporary function adagrad_rda as 'hivemall.classifier.AdaGradRDAUDTF';
-drop temporary function cosine_sim;
+drop temporary function if exists cosine_sim;
create temporary function cosine_sim as 'hivemall.knn.similarity.CosineSimilarityUDF';
-drop temporary function jaccard;
+drop temporary function if exists jaccard;
create temporary function jaccard as 'hivemall.knn.similarity.JaccardIndexUDF';
-drop temporary function wvoted_avg;
+drop temporary function if exists wvoted_avg;
create temporary function wvoted_avg as 'hivemall.ensemble.bagging.WeightVotedAvgUDAF';
-drop temporary function sortByFeature;
+drop temporary function if exists sortByFeature;
create temporary function sortByFeature as 'hivemall.ftvec.SortByFeatureUDF';
-drop temporary function train_logregr;
+drop temporary function if exists train_logregr;
create temporary function train_logregr as 'hivemall.regression.LogressUDTF';
-drop temporary function pa1_regress;
+drop temporary function if exists pa1_regress;
create temporary function pa1_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF';
-drop temporary function pa1a_regress;
+drop temporary function if exists pa1a_regress;
create temporary function pa1a_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA1a';
-drop temporary function pa2_regress;
+drop temporary function if exists pa2_regress;
create temporary function pa2_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA2';
-drop temporary function pa2a_regress;
+drop temporary function if exists pa2a_regress;
create temporary function pa2a_regress as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA2a';
-drop temporary function arow_regress;
+drop temporary function if exists arow_regress;
create temporary function arow_regress as 'hivemall.regression.AROWRegressionUDTF';
-drop temporary function arowe_regress;
+drop temporary function if exists arowe_regress;
create temporary function arowe_regress as 'hivemall.regression.AROWRegressionUDTF$AROWe';
-drop temporary function arowe2_regress;
+drop temporary function if exists arowe2_regress;
create temporary function arowe2_regress as 'hivemall.regression.AROWRegressionUDTF$AROWe2';
-drop temporary function adagrad_regr;
+drop temporary function if exists adagrad_regr;
create temporary function adagrad_regr as 'hivemall.regression.AdaGradUDTF';
-drop temporary function adagrad;
+drop temporary function if exists adagrad;
create temporary function adagrad as 'hivemall.regression.AdaGradUDTF';
-drop temporary function train_adadelta;
+drop temporary function if exists train_adadelta;
create temporary function train_adadelta as 'hivemall.regression.AdaDeltaUDTF';
-drop temporary function adadelta;
+drop temporary function if exists adadelta;
create temporary function adadelta as 'hivemall.regression.AdaDeltaUDTF';
-drop temporary function collect_all;
+drop temporary function if exists collect_all;
create temporary function collect_all as 'hivemall.tools.array.CollectAllUDAF';
-drop temporary function vm_tree_predict;
+drop temporary function if exists vm_tree_predict;
create temporary function vm_tree_predict as 'hivemall.smile.tools.TreePredictByStackMachineUDF';
-drop temporary function js_tree_predict;
+drop temporary function if exists js_tree_predict;
create temporary function js_tree_predict as 'hivemall.smile.tools.TreePredictByJavascriptUDF';
-drop temporary function train_gbt_classifier;
+drop temporary function if exists train_gbt_classifier;
create temporary function train_gbt_classifier as 'hivemall.smile.classification.GradientTreeBoostingClassifierUDTF';
-drop temporary function train_arowh;
+drop temporary function if exists train_arowh;
create temporary function train_arowh as 'hivemall.classifier.AROWClassifierUDTF$AROWh';
-drop temporary function normalize;
+drop temporary function if exists normalize;
create temporary function normalize as 'hivemall.ftvec.scaling.L2NormalizationUDF';
-drop temporary function train_adagrad;
+drop temporary function if exists train_adagrad;
create temporary function train_adagrad as 'hivemall.regression.AdaGradUDTF';
-drop temporary function rescale_fv;
+drop temporary function if exists rescale_fv;
create temporary function rescale_fv as 'hivemall.ftvec.scaling.RescaleUDF';
-drop temporary function addBias;
+drop temporary function if exists addBias;
create temporary function addBias as 'hivemall.ftvec.AddBiasUDF';
-drop temporary function sha1;
+drop temporary function if exists sha1;
create temporary function sha1 as 'hivemall.ftvec.hashing.Sha1UDF';
http://git-wip-us.apache.org/repos/asf/incubator-hivemall/blob/231f4e05/resources/ddl/define-all.hive
----------------------------------------------------------------------
diff --git a/resources/ddl/define-all.hive b/resources/ddl/define-all.hive
index b8ff709..9cc348f 100644
--- a/resources/ddl/define-all.hive
+++ b/resources/ddl/define-all.hive
@@ -2,618 +2,618 @@
-- Hivemall: Hive scalable Machine Learning Library
-----------------------------------------------------------------------------
-drop temporary function hivemall_version;
+drop temporary function if exists hivemall_version;
create temporary function hivemall_version as 'hivemall.HivemallVersionUDF';
---------------------------
-- binary classification --
---------------------------
-drop temporary function train_perceptron;
+drop temporary function if exists train_perceptron;
create temporary function train_perceptron as 'hivemall.classifier.PerceptronUDTF';
-drop temporary function train_pa;
+drop temporary function if exists train_pa;
create temporary function train_pa as 'hivemall.classifier.PassiveAggressiveUDTF';
-drop temporary function train_pa1;
+drop temporary function if exists train_pa1;
create temporary function train_pa1 as 'hivemall.classifier.PassiveAggressiveUDTF$PA1';
-drop temporary function train_pa2;
+drop temporary function if exists train_pa2;
create temporary function train_pa2 as 'hivemall.classifier.PassiveAggressiveUDTF$PA2';
-drop temporary function train_cw;
+drop temporary function if exists train_cw;
create temporary function train_cw as 'hivemall.classifier.ConfidenceWeightedUDTF';
-drop temporary function train_arow;
+drop temporary function if exists train_arow;
create temporary function train_arow as 'hivemall.classifier.AROWClassifierUDTF';
-drop temporary function train_arowh;
+drop temporary function if exists train_arowh;
create temporary function train_arowh as 'hivemall.classifier.AROWClassifierUDTF$AROWh';
-drop temporary function train_scw;
+drop temporary function if exists train_scw;
create temporary function train_scw as 'hivemall.classifier.SoftConfideceWeightedUDTF$SCW1';
-drop temporary function train_scw2;
+drop temporary function if exists train_scw2;
create temporary function train_scw2 as 'hivemall.classifier.SoftConfideceWeightedUDTF$SCW2';
-drop temporary function train_adagrad_rda;
+drop temporary function if exists train_adagrad_rda;
create temporary function train_adagrad_rda as 'hivemall.classifier.AdaGradRDAUDTF';
-drop temporary function train_kpa;
+drop temporary function if exists train_kpa;
create temporary function train_kpa as 'hivemall.classifier.KernelExpansionPassiveAggressiveUDTF';
-drop temporary function kpa_predict;
+drop temporary function if exists kpa_predict;
create temporary function kpa_predict as 'hivemall.classifier.KPAPredictUDAF';
--------------------------------
-- Multiclass classification --
--------------------------------
-drop temporary function train_multiclass_perceptron;
+drop temporary function if exists train_multiclass_perceptron;
create temporary function train_multiclass_perceptron as 'hivemall.classifier.multiclass.MulticlassPerceptronUDTF';
-drop temporary function train_multiclass_pa;
+drop temporary function if exists train_multiclass_pa;
create temporary function train_multiclass_pa as 'hivemall.classifier.multiclass.MulticlassPassiveAggressiveUDTF';
-drop temporary function train_multiclass_pa1;
+drop temporary function if exists train_multiclass_pa1;
create temporary function train_multiclass_pa1 as 'hivemall.classifier.multiclass.MulticlassPassiveAggressiveUDTF$PA1';
-drop temporary function train_multiclass_pa2;
+drop temporary function if exists train_multiclass_pa2;
create temporary function train_multiclass_pa2 as 'hivemall.classifier.multiclass.MulticlassPassiveAggressiveUDTF$PA2';
-drop temporary function train_multiclass_cw;
+drop temporary function if exists train_multiclass_cw;
create temporary function train_multiclass_cw as 'hivemall.classifier.multiclass.MulticlassConfidenceWeightedUDTF';
-drop temporary function train_multiclass_arow;
+drop temporary function if exists train_multiclass_arow;
create temporary function train_multiclass_arow as 'hivemall.classifier.multiclass.MulticlassAROWClassifierUDTF';
-drop temporary function train_multiclass_arowh;
+drop temporary function if exists train_multiclass_arowh;
create temporary function train_multiclass_arowh as 'hivemall.classifier.multiclass.MulticlassAROWClassifierUDTF$AROWh';
-drop temporary function train_multiclass_scw;
+drop temporary function if exists train_multiclass_scw;
create temporary function train_multiclass_scw as 'hivemall.classifier.multiclass.MulticlassSoftConfidenceWeightedUDTF$SCW1';
-drop temporary function train_multiclass_scw2;
+drop temporary function if exists train_multiclass_scw2;
create temporary function train_multiclass_scw2 as 'hivemall.classifier.multiclass.MulticlassSoftConfidenceWeightedUDTF$SCW2';
--------------------------
-- similarity functions --
--------------------------
-drop temporary function cosine_similarity;
+drop temporary function if exists cosine_similarity;
create temporary function cosine_similarity as 'hivemall.knn.similarity.CosineSimilarityUDF';
-drop temporary function jaccard_similarity;
+drop temporary function if exists jaccard_similarity;
create temporary function jaccard_similarity as 'hivemall.knn.similarity.JaccardIndexUDF';
-drop temporary function angular_similarity;
+drop temporary function if exists angular_similarity;
create temporary function angular_similarity as 'hivemall.knn.similarity.AngularSimilarityUDF';
-drop temporary function euclid_similarity;
+drop temporary function if exists euclid_similarity;
create temporary function euclid_similarity as 'hivemall.knn.similarity.EuclidSimilarity';
-drop temporary function distance2similarity;
+drop temporary function if exists distance2similarity;
create temporary function distance2similarity as 'hivemall.knn.similarity.Distance2SimilarityUDF';
------------------------
-- distance functions --
------------------------
-drop temporary function popcnt;
+drop temporary function if exists popcnt;
create temporary function popcnt as 'hivemall.knn.distance.PopcountUDF';
-drop temporary function kld;
+drop temporary function if exists kld;
create temporary function kld as 'hivemall.knn.distance.KLDivergenceUDF';
-drop temporary function hamming_distance;
+drop temporary function if exists hamming_distance;
create temporary function hamming_distance as 'hivemall.knn.distance.HammingDistanceUDF';
-drop temporary function euclid_distance;
+drop temporary function if exists euclid_distance;
create temporary function euclid_distance as 'hivemall.knn.distance.EuclidDistanceUDF';
-drop temporary function cosine_distance;
+drop temporary function if exists cosine_distance;
create temporary function cosine_distance as 'hivemall.knn.distance.CosineDistanceUDF';
-drop temporary function angular_distance;
+drop temporary function if exists angular_distance;
create temporary function angular_distance as 'hivemall.knn.distance.AngularDistanceUDF';
-drop temporary function jaccard_distance;
+drop temporary function if exists jaccard_distance;
create temporary function jaccard_distance as 'hivemall.knn.distance.JaccardDistanceUDF';
-drop temporary function manhattan_distance;
+drop temporary function if exists manhattan_distance;
create temporary function manhattan_distance as 'hivemall.knn.distance.ManhattanDistanceUDF';
-drop temporary function minkowski_distance;
+drop temporary function if exists minkowski_distance;
create temporary function minkowski_distance as 'hivemall.knn.distance.MinkowskiDistanceUDF';
-------------------
-- LSH functions --
-------------------
-drop temporary function minhashes;
+drop temporary function if exists minhashes;
create temporary function minhashes as 'hivemall.knn.lsh.MinHashesUDF';
-drop temporary function minhash;
+drop temporary function if exists minhash;
create temporary function minhash as 'hivemall.knn.lsh.MinHashUDTF';
-drop temporary function bbit_minhash;
+drop temporary function if exists bbit_minhash;
create temporary function bbit_minhash as 'hivemall.knn.lsh.bBitMinHashUDF';
----------------------
-- voting functions --
----------------------
-drop temporary function voted_avg;
+drop temporary function if exists voted_avg;
create temporary function voted_avg as 'hivemall.ensemble.bagging.VotedAvgUDAF';
-drop temporary function weight_voted_avg;
+drop temporary function if exists weight_voted_avg;
create temporary function weight_voted_avg as 'hivemall.ensemble.bagging.WeightVotedAvgUDAF';
--------------------
-- misc functions --
--------------------
-drop temporary function max_label;
+drop temporary function if exists max_label;
create temporary function max_label as 'hivemall.ensemble.MaxValueLabelUDAF';
-drop temporary function maxrow;
+drop temporary function if exists maxrow;
create temporary function maxrow as 'hivemall.ensemble.MaxRowUDAF';
-drop temporary function argmin_kld;
+drop temporary function if exists argmin_kld;
create temporary function argmin_kld as 'hivemall.ensemble.ArgminKLDistanceUDAF';
-----------------------
-- hashing functions --
-----------------------
-drop temporary function mhash;
+drop temporary function if exists mhash;
create temporary function mhash as 'hivemall.ftvec.hashing.MurmurHash3UDF';
-drop temporary function array_hash_values;
+drop temporary function if exists array_hash_values;
create temporary function array_hash_values as 'hivemall.ftvec.hashing.ArrayHashValuesUDF';
-drop temporary function prefixed_hash_values;
+drop temporary function if exists prefixed_hash_values;
create temporary function prefixed_hash_values as 'hivemall.ftvec.hashing.ArrayPrefixedHashValuesUDF';
-drop temporary function feature_hashing;
+drop temporary function if exists feature_hashing;
create temporary function feature_hashing as 'hivemall.ftvec.hashing.FeatureHashingUDF';
-----------------------
-- pairing functions --
-----------------------
-drop temporary function polynomial_features;
+drop temporary function if exists polynomial_features;
create temporary function polynomial_features as 'hivemall.ftvec.pairing.PolynomialFeaturesUDF';
-drop temporary function powered_features;
+drop temporary function if exists powered_features;
create temporary function powered_features as 'hivemall.ftvec.pairing.PoweredFeaturesUDF';
-drop temporary function feature_pairs;
+drop temporary function if exists feature_pairs;
create temporary function feature_pairs as 'hivemall.ftvec.pairing.FeaturePairsUDTF';
-----------------------
-- scaling functions --
-----------------------
-drop temporary function rescale;
+drop temporary function if exists rescale;
create temporary function rescale as 'hivemall.ftvec.scaling.RescaleUDF';
-drop temporary function zscore;
+drop temporary function if exists zscore;
create temporary function zscore as 'hivemall.ftvec.scaling.ZScoreUDF';
-drop temporary function l2_normalize;
+drop temporary function if exists l2_normalize;
create temporary function l2_normalize as 'hivemall.ftvec.scaling.L2NormalizationUDF';
---------------------------------
-- Feature Selection functions --
---------------------------------
-drop temporary function chi2;
+drop temporary function if exists chi2;
create temporary function chi2 as 'hivemall.ftvec.selection.ChiSquareUDF';
-drop temporary function snr;
+drop temporary function if exists snr;
create temporary function snr as 'hivemall.ftvec.selection.SignalNoiseRatioUDAF';
-----------------------------------
-- Feature engineering functions --
-----------------------------------
-drop temporary function amplify;
+drop temporary function if exists amplify;
create temporary function amplify as 'hivemall.ftvec.amplify.AmplifierUDTF';
-drop temporary function rand_amplify;
+drop temporary function if exists rand_amplify;
create temporary function rand_amplify as 'hivemall.ftvec.amplify.RandomAmplifierUDTF';
-drop temporary function add_bias;
+drop temporary function if exists add_bias;
create temporary function add_bias as 'hivemall.ftvec.AddBiasUDF';
-drop temporary function sort_by_feature;
+drop temporary function if exists sort_by_feature;
create temporary function sort_by_feature as 'hivemall.ftvec.SortByFeatureUDF';
-drop temporary function extract_feature;
+drop temporary function if exists extract_feature;
create temporary function extract_feature as 'hivemall.ftvec.ExtractFeatureUDF';
-drop temporary function extract_weight;
+drop temporary function if exists extract_weight;
create temporary function extract_weight as 'hivemall.ftvec.ExtractWeightUDF';
-drop temporary function add_feature_index;
+drop temporary function if exists add_feature_index;
create temporary function add_feature_index as 'hivemall.ftvec.AddFeatureIndexUDF';
-drop temporary function feature;
+drop temporary function if exists feature;
create temporary function feature as 'hivemall.ftvec.FeatureUDF';
-drop temporary function feature_index;
+drop temporary function if exists feature_index;
create temporary function feature_index as 'hivemall.ftvec.FeatureIndexUDF';
----------------------------------
-- feature converting functions --
----------------------------------
-drop temporary function conv2dense;
+drop temporary function if exists conv2dense;
create temporary function conv2dense as 'hivemall.ftvec.conv.ConvertToDenseModelUDAF';
-drop temporary function to_dense_features;
+drop temporary function if exists to_dense_features;
create temporary function to_dense_features as 'hivemall.ftvec.conv.ToDenseFeaturesUDF';
-- alias
-drop temporary function to_dense;
+drop temporary function if exists to_dense;
create temporary function to_dense as 'hivemall.ftvec.conv.ToDenseFeaturesUDF';
-drop temporary function to_sparse_features;
+drop temporary function if exists to_sparse_features;
create temporary function to_sparse_features as 'hivemall.ftvec.conv.ToSparseFeaturesUDF';
-- alias
-drop temporary function to_sparse;
+drop temporary function if exists to_sparse;
create temporary function to_sparse as 'hivemall.ftvec.conv.ToSparseFeaturesUDF';
-drop temporary function quantify;
+drop temporary function if exists quantify;
create temporary function quantify as 'hivemall.ftvec.conv.QuantifyColumnsUDTF';
-drop temporary function build_bins;
+drop temporary function if exists build_bins;
create temporary function build_bins as 'hivemall.ftvec.binning.BuildBinsUDAF';
-drop temporary function feature_binning;
+drop temporary function if exists feature_binning;
create temporary function feature_binning as 'hivemall.ftvec.binning.FeatureBinningUDF';
--------------------------
-- feature transformers --
--------------------------
-drop temporary function vectorize_features;
+drop temporary function if exists vectorize_features;
create temporary function vectorize_features as 'hivemall.ftvec.trans.VectorizeFeaturesUDF';
-drop temporary function categorical_features;
+drop temporary function if exists categorical_features;
create temporary function categorical_features as 'hivemall.ftvec.trans.CategoricalFeaturesUDF';
-drop temporary function ffm_features;
+drop temporary function if exists ffm_features;
create temporary function ffm_features as 'hivemall.ftvec.trans.FFMFeaturesUDF';
-drop temporary function indexed_features;
+drop temporary function if exists indexed_features;
create temporary function indexed_features as 'hivemall.ftvec.trans.IndexedFeatures';
-drop temporary function quantified_features;
+drop temporary function if exists quantified_features;
create temporary function quantified_features as 'hivemall.ftvec.trans.QuantifiedFeaturesUDTF';
-drop temporary function quantitative_features;
+drop temporary function if exists quantitative_features;
create temporary function quantitative_features as 'hivemall.ftvec.trans.QuantitativeFeaturesUDF';
-drop temporary function binarize_label;
+drop temporary function if exists binarize_label;
create temporary function binarize_label as 'hivemall.ftvec.trans.BinarizeLabelUDTF';
-drop temporary function onehot_encoding;
+drop temporary function if exists onehot_encoding;
create temporary function onehot_encoding as 'hivemall.ftvec.trans.OnehotEncodingUDAF';
------------------------------
-- ranking helper functions --
------------------------------
-drop temporary function bpr_sampling;
+drop temporary function if exists bpr_sampling;
create temporary function bpr_sampling as 'hivemall.ftvec.ranking.BprSamplingUDTF';
-drop temporary function item_pairs_sampling;
+drop temporary function if exists item_pairs_sampling;
create temporary function item_pairs_sampling as 'hivemall.ftvec.ranking.ItemPairsSamplingUDTF';
-drop temporary function populate_not_in;
+drop temporary function if exists populate_not_in;
create temporary function populate_not_in as 'hivemall.ftvec.ranking.PopulateNotInUDTF';
--------------------------
-- ftvec/text functions --
--------------------------
-drop temporary function tf;
+drop temporary function if exists tf;
create temporary function tf as 'hivemall.ftvec.text.TermFrequencyUDAF';
--------------------------
-- Regression functions --
--------------------------
-drop temporary function logress;
+drop temporary function if exists logress;
create temporary function logress as 'hivemall.regression.LogressUDTF';
-drop temporary function train_logistic_regr;
+drop temporary function if exists train_logistic_regr;
create temporary function train_logistic_regr as 'hivemall.regression.LogressUDTF';
-drop temporary function train_pa1_regr;
+drop temporary function if exists train_pa1_regr;
create temporary function train_pa1_regr as 'hivemall.regression.PassiveAggressiveRegressionUDTF';
-drop temporary function train_pa1a_regr;
+drop temporary function if exists train_pa1a_regr;
create temporary function train_pa1a_regr as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA1a';
-drop temporary function train_pa2_regr;
+drop temporary function if exists train_pa2_regr;
create temporary function train_pa2_regr as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA2';
-drop temporary function train_pa2a_regr;
+drop temporary function if exists train_pa2a_regr;
create temporary function train_pa2a_regr as 'hivemall.regression.PassiveAggressiveRegressionUDTF$PA2a';
-drop temporary function train_arow_regr;
+drop temporary function if exists train_arow_regr;
create temporary function train_arow_regr as 'hivemall.regression.AROWRegressionUDTF';
-drop temporary function train_arowe_regr;
+drop temporary function if exists train_arowe_regr;
create temporary function train_arowe_regr as 'hivemall.regression.AROWRegressionUDTF$AROWe';
-drop temporary function train_arowe2_regr;
+drop temporary function if exists train_arowe2_regr;
create temporary function train_arowe2_regr as 'hivemall.regression.AROWRegressionUDTF$AROWe2';
-drop temporary function train_adagrad_regr;
+drop temporary function if exists train_adagrad_regr;
create temporary function train_adagrad_regr as 'hivemall.regression.AdaGradUDTF';
-drop temporary function train_adadelta_regr;
+drop temporary function if exists train_adadelta_regr;
create temporary function train_adadelta_regr as 'hivemall.regression.AdaDeltaUDTF';
---------------------
-- array functions --
---------------------
-drop temporary function float_array;
+drop temporary function if exists float_array;
create temporary function float_array as 'hivemall.tools.array.AllocFloatArrayUDF';
-drop temporary function array_remove;
+drop temporary function if exists array_remove;
create temporary function array_remove as 'hivemall.tools.array.ArrayRemoveUDF';
-drop temporary function sort_and_uniq_array;
+drop temporary function if exists sort_and_uniq_array;
create temporary function sort_and_uniq_array as 'hivemall.tools.array.SortAndUniqArrayUDF';
-drop temporary function subarray_endwith;
+drop temporary function if exists subarray_endwith;
create temporary function subarray_endwith as 'hivemall.tools.array.SubarrayEndWithUDF';
-drop temporary function subarray_startwith;
+drop temporary function if exists subarray_startwith;
create temporary function subarray_startwith as 'hivemall.tools.array.SubarrayStartWithUDF';
-drop temporary function array_concat;
+drop temporary function if exists array_concat;
create temporary function array_concat as 'hivemall.tools.array.ArrayConcatUDF';
-- alias for backward compatibility
-drop temporary function concat_array;
+drop temporary function if exists concat_array;
create temporary function concat_array as 'hivemall.tools.array.ArrayConcatUDF';
-drop temporary function subarray;
+drop temporary function if exists subarray;
create temporary function subarray as 'hivemall.tools.array.SubarrayUDF';
-drop temporary function array_avg;
+drop temporary function if exists array_avg;
create temporary function array_avg as 'hivemall.tools.array.ArrayAvgGenericUDAF';
-drop temporary function array_sum;
+drop temporary function if exists array_sum;
create temporary function array_sum as 'hivemall.tools.array.ArraySumUDAF';
-drop temporary function to_string_array;
+drop temporary function if exists to_string_array;
create temporary function to_string_array as 'hivemall.tools.array.ToStringArrayUDF';
-drop temporary function array_intersect;
+drop temporary function if exists array_intersect;
create temporary function array_intersect as 'hivemall.tools.array.ArrayIntersectUDF';
-drop temporary function select_k_best;
+drop temporary function if exists select_k_best;
create temporary function select_k_best as 'hivemall.tools.array.SelectKBestUDF';
-----------------------------
-- bit operation functions --
-----------------------------
-drop temporary function bits_collect;
+drop temporary function if exists bits_collect;
create temporary function bits_collect as 'hivemall.tools.bits.BitsCollectUDAF';
-drop temporary function to_bits;
+drop temporary function if exists to_bits;
create temporary function to_bits as 'hivemall.tools.bits.ToBitsUDF';
-drop temporary function unbits;
+drop temporary function if exists unbits;
create temporary function unbits as 'hivemall.tools.bits.UnBitsUDF';
-drop temporary function bits_or;
+drop temporary function if exists bits_or;
create temporary function bits_or as 'hivemall.tools.bits.BitsORUDF';
---------------------------
-- compression functions --
---------------------------
-drop temporary function inflate;
+drop temporary function if exists inflate;
create temporary function inflate as 'hivemall.tools.compress.InflateUDF';
-drop temporary function deflate;
+drop temporary function if exists deflate;
create temporary function deflate as 'hivemall.tools.compress.DeflateUDF';
---------------------
-- map functions --
---------------------
-drop temporary function map_get_sum;
+drop temporary function if exists map_get_sum;
create temporary function map_get_sum as 'hivemall.tools.map.MapGetSumUDF';
-drop temporary function map_tail_n;
+drop temporary function if exists map_tail_n;
create temporary function map_tail_n as 'hivemall.tools.map.MapTailNUDF';
-drop temporary function to_map;
+drop temporary function if exists to_map;
create temporary function to_map as 'hivemall.tools.map.UDAFToMap';
-drop temporary function to_ordered_map;
+drop temporary function if exists to_ordered_map;
create temporary function to_ordered_map as 'hivemall.tools.map.UDAFToOrderedMap';
---------------------
-- Math functions --
---------------------
-drop temporary function sigmoid;
+drop temporary function if exists sigmoid;
create temporary function sigmoid as 'hivemall.tools.math.SigmoidGenericUDF';
----------------------
-- Matrix functions --
----------------------
-drop temporary function transpose_and_dot;
+drop temporary function if exists transpose_and_dot;
create temporary function transpose_and_dot as 'hivemall.tools.matrix.TransposeAndDotUDAF';
----------------------
-- mapred functions --
----------------------
-drop temporary function taskid;
+drop temporary function if exists taskid;
create temporary function taskid as 'hivemall.tools.mapred.TaskIdUDF';
-drop temporary function jobid;
+drop temporary function if exists jobid;
create temporary function jobid as 'hivemall.tools.mapred.JobIdUDF';
-drop temporary function rowid;
+drop temporary function if exists rowid;
create temporary function rowid as 'hivemall.tools.mapred.RowIdUDF';
-drop temporary function distcache_gets;
+drop temporary function if exists distcache_gets;
create temporary function distcache_gets as 'hivemall.tools.mapred.DistributedCacheLookupUDF';
-drop temporary function jobconf_gets;
+drop temporary function if exists jobconf_gets;
create temporary function jobconf_gets as 'hivemall.tools.mapred.JobConfGetsUDF';
--------------------
-- misc functions --
--------------------
-drop temporary function generate_series;
+drop temporary function if exists generate_series;
create temporary function generate_series as 'hivemall.tools.GenerateSeriesUDTF';
-drop temporary function convert_label;
+drop temporary function if exists convert_label;
create temporary function convert_label as 'hivemall.tools.ConvertLabelUDF';
-drop temporary function x_rank;
+drop temporary function if exists x_rank;
create temporary function x_rank as 'hivemall.tools.RankSequenceUDF';
-drop temporary function each_top_k;
+drop temporary function if exists each_top_k;
create temporary function each_top_k as 'hivemall.tools.EachTopKUDTF';
-------------------------------
-- Text processing functions --
-------------------------------
-drop temporary function tokenize;
+drop temporary function if exists tokenize;
create temporary function tokenize as 'hivemall.tools.text.TokenizeUDF';
-drop temporary function is_stopword;
+drop temporary function if exists is_stopword;
create temporary function is_stopword as 'hivemall.tools.text.StopwordUDF';
-drop temporary function split_words;
+drop temporary function if exists split_words;
create temporary function split_words as 'hivemall.tools.text.SplitWordsUDF';
-drop temporary function normalize_unicode;
+drop temporary function if exists normalize_unicode;
create temporary function normalize_unicode as 'hivemall.tools.text.NormalizeUnicodeUDF';
-drop temporary function base91;
+drop temporary function if exists base91;
create temporary function base91 as 'hivemall.tools.text.Base91UDF';
-drop temporary function unbase91;
+drop temporary function if exists unbase91;
create temporary function unbase91 as 'hivemall.tools.text.Unbase91UDF';
---------------------------------
-- Dataset generator functions --
---------------------------------
-drop temporary function lr_datagen;
+drop temporary function if exists lr_datagen;
create temporary function lr_datagen as 'hivemall.dataset.LogisticRegressionDataGeneratorUDTF';
--------------------------
-- Evaluating functions --
--------------------------
-drop temporary function f1score;
+drop temporary function if exists f1score;
create temporary function f1score as 'hivemall.evaluation.FMeasureUDAF';
-drop temporary function mae;
+drop temporary function if exists mae;
create temporary function mae as 'hivemall.evaluation.MeanAbsoluteErrorUDAF';
-drop temporary function mse;
+drop temporary function if exists mse;
create temporary function mse as 'hivemall.evaluation.MeanSquaredErrorUDAF';
-drop temporary function rmse;
+drop temporary function if exists rmse;
create temporary function rmse as 'hivemall.evaluation.RootMeanSquaredErrorUDAF';
-drop temporary function r2;
+drop temporary function if exists r2;
create temporary function r2 as 'hivemall.evaluation.R2UDAF';
-drop temporary function ndcg;
+drop temporary function if exists ndcg;
create temporary function ndcg as 'hivemall.evaluation.NDCGUDAF';
-drop temporary function logloss;
+drop temporary function if exists logloss;
create temporary function logloss as 'hivemall.evaluation.LogarithmicLossUDAF';
--------------------------
-- Matrix Factorization --
--------------------------
-drop temporary function mf_predict;
+drop temporary function if exists mf_predict;
create temporary function mf_predict as 'hivemall.mf.MFPredictionUDF';
-drop temporary function train_mf_sgd;
+drop temporary function if exists train_mf_sgd;
create temporary function train_mf_sgd as 'hivemall.mf.MatrixFactorizationSGDUDTF';
-drop temporary function train_mf_adagrad;
+drop temporary function if exists train_mf_adagrad;
create temporary function train_mf_adagrad as 'hivemall.mf.MatrixFactorizationAdaGradUDTF';
-drop temporary function train_bprmf;
+drop temporary function if exists train_bprmf;
create temporary function train_bprmf as 'hivemall.mf.BPRMatrixFactorizationUDTF';
-drop temporary function bprmf_predict;
+drop temporary function if exists bprmf_predict;
create temporary function bprmf_predict as 'hivemall.mf.BPRMFPredictionUDF';
---------------------------
-- Factorization Machine --
---------------------------
-drop temporary function fm_predict;
+drop temporary function if exists fm_predict;
create temporary function fm_predict as 'hivemall.fm.FMPredictGenericUDAF';
-drop temporary function train_fm;
+drop temporary function if exists train_fm;
create temporary function train_fm as 'hivemall.fm.FactorizationMachineUDTF';
-drop temporary function train_ffm;
+drop temporary function if exists train_ffm;
create temporary function train_ffm as 'hivemall.fm.FieldAwareFactorizationMachineUDTF';
-drop temporary function ffm_predict;
+drop temporary function if exists ffm_predict;
create temporary function ffm_predict as 'hivemall.fm.FFMPredictUDF';
---------------------------
-- Anomaly Detection ------
---------------------------
-drop temporary function changefinder;
+drop temporary function if exists changefinder;
create temporary function changefinder as 'hivemall.anomaly.ChangeFinderUDF';
-drop temporary function sst;
+drop temporary function if exists sst;
create temporary function sst as 'hivemall.anomaly.SingularSpectrumTransformUDF';
----------------------------
-- Smile related features --
----------------------------
-drop temporary function train_randomforest_classifier;
+drop temporary function if exists train_randomforest_classifier;
create temporary function train_randomforest_classifier as 'hivemall.smile.classification.RandomForestClassifierUDTF';
-drop temporary function train_randomforest_regressor;
+drop temporary function if exists train_randomforest_regressor;
create temporary function train_randomforest_regressor as 'hivemall.smile.regression.RandomForestRegressionUDTF';
-drop temporary function train_randomforest_regr;
+drop temporary function if exists train_randomforest_regr;
create temporary function train_randomforest_regr as 'hivemall.smile.regression.RandomForestRegressionUDTF';
-drop temporary function tree_predict;
+drop temporary function if exists tree_predict;
create temporary function tree_predict as 'hivemall.smile.tools.TreePredictUDF';
-drop temporary function rf_ensemble;
+drop temporary function if exists rf_ensemble;
create temporary function rf_ensemble as 'hivemall.smile.tools.RandomForestEnsembleUDAF';
-drop temporary function guess_attribute_types;
+drop temporary function if exists guess_attribute_types;
create temporary function guess_attribute_types as 'hivemall.smile.tools.GuessAttributesUDF';
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