examples/src/main/r/ml/lda.R

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# To run this example use
# ./bin/spark-submit examples/src/main/r/ml/lda.R

# Load SparkR library into your R session
library(SparkR)

# Initialize SparkSession
sparkR.session(appName = "SparkR-ML-lda-example")

# $example on$
# Load training data
df <- read.df("data/mllib/sample_lda_libsvm_data.txt", source = "libsvm")
training <- df
test <- df

# Fit a latent dirichlet allocation model with spark.lda
model <- spark.lda(training, k = 10, maxIter = 10)

# Model summary
summary(model)

# Posterior probabilities
posterior <- spark.posterior(model, test)
head(posterior)

# The log perplexity of the LDA model
logPerplexity <- spark.perplexity(model, test)
print(paste0("The upper bound bound on perplexity: ", logPerplexity))
# $example off$

sparkR.session.stop()