Is it efficient to cache a dataframe for a single Action Spark application in which that dataframe is referenced more than once?

I am little confused with the caching mechanism of Spark. Let’s say I have a Spark application with only one action at the end of multiple transformations. In which suppose I have a dataframe A and I applied 2-3 transformation on it, creating multiple dataframes which eventually helps creating a last dataframe which is going…

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How to turn the color scale in Plotly r to log scale

I am trying to have a logarithmic scale for the color bar in R, any ideas on how I can do it? My code: TEST_DATAFRAME = read.table(TEST_FILE, sep=”\t”,skip=2, header=T) PROD_DATAFRAME = read.table(PROD_FILE, sep=”\t”,skip=2, header=T) PARAMETER = “Vf_High” LST_RESIDUAL <- PROD_DATAFRAME[PARAMETER] – TEST_DATAFRAME[PARAMETER] PARAM_DATAFRAME <- data.frame(“NEW_MEASUREMENT” = TEST_DATAFRAME[PARAMETER], “OLD_MEASUREMENT” = PROD_DATAFRAME[PARAMETER], “RESIDUAL” = LST_RESIDUAL) colnames(PARAM_DATAFRAME) <-…

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Connecting a GPS/GLONASS U-blox7 via USB gives “Could not grab port (tty/ttyACM0)”

I am trying to read data from a U-blox 7 but i am getting the message “Could not grab port (tty/ttyACM0)” So far I’ve created the file to modify the kernel 49-ublox.rules which contains the following: ATTRS{idVendor}==”1546″, ATTRS{idProduct}==”01a7″, ENV{ID_MM_DEVICE_IGNORE}=”1″ ATTRS{idVendor}==”1546″, ATTRS{idProduct}==”01a7″, ENV{MTP_NO_PROBE}=”1″ SUBSYSTEMS==”usb”, ATTRS{idVendor}==”1546″, ATTRS{idProduct}==”01a7″, MODE:=”0666″ KERNEL==”ttyACM*”, ATTRS{idVendor}==”1546″, ATTRS{idProduct}==”01a7″, MODE:=”0666″ But still I am not…

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Bundle(identifier: “org.cocoapods.MyPrivatePod”) return nil

I would like to access to my private pod bundle, but always return nil. Bundle(identifier: “org.cocoapods.MyPrivatePod”)//only this return nil Bundle(identifier: “org.cocoapods.Alamofire”) Bundle(identifier: “org.cocoapods.SQLCipher”) My podspec Pod::Spec.new do |s| s.name = ‘MyPrivatePod’ s.version = ‘1.4.0’ s.summary = ‘MyPrivatePod Component’ s.description = “MyPrivatePod.” s.homepage = ‘https://github.com/myprivatecompany/myprivtepodrepo.git’ s.license = “” s.authors = { ‘me me’ => ‘me@me.com’ }…

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Get embedding vectors from Embedding Column in Tensorflow

I want to get the numpy vectors created using the “Embedding Column” in Tensorflow. For example, creating a sample DF: sample_column1 = [“Apple”,”Apple”,”Mango”,”Apple”,”Banana”,”Mango”,”Mango”,”Banana”,”Banana”] sample_column2 = [1,2,1,3,4,6,2,1,3] ds = pd.DataFrame(sample_column1,columns=[“A”]) ds[“B”] = sample_column2 ds Converting the pandas DF to Tensorflow object # A utility method to create a tf.data dataset from a Pandas Dataframe def df_to_dataset(dataframe,…

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