We are collecting JSON data (public social media posts in particular) via REST API invocations, which we plan to dump into HDFS, then abstract a Hive table on top it using SerDe. I wonder though what would be the appropriate delimiter per JSON entry in a file? Is it new line ("\n")? So it would look like this:
{ id: entry1 ... post: }
{ id: entry2 ... post: }
...
{ id: entryn ... post: }
How about if we encounter a new line character within the JSON data itself, for example in post?
The best way would be one record per line, separated by "\n" exactly as you guessed.
This also means that you should be careful to escape "\n" that may be inside the JSON elements.
Indented JSON won't work well with hadoop/hive, since to distribute processing, hadoop must be able to tell when a records ends, so it can split processing of a file with N bytes with W workers in W chunks of size roughly N/W.
The splitting is done by the particular InputFormat that's been used, in case of text, TextInputFormat.
TextInputFormat will basically split the file at the first instance of "\n" found after byte i*N/W (for i from 1 to W-1).
For this reason, having other "\n" around would confuse Hadoop and it will give you incomplete records.
As an alternative, I wouldn't recommend it, but if you really wanted you could use a character other than "\n" by configuring the property "textinputformat.record.delimiter" when reading the file through hadoop/hive, using a character that won't be in JSON (for instance, \001 or CTRL-A is commonly used by Hive as a field delimiter) but that can be tricky since it has to also be supported by the SerDe.
Also, if you change the record delimiter, anybody who copies/uses the file on HDFS must be aware of the delimiter, or they won't be able to parse it correctly, and will need special code to do it, while keeping "\n" as a delimiter, the files will still be normal text files and can be used by other tools.
As for the SerDe, I'd recommend this one, with the disclaimer that I wrote it :)
https://github.com/rcongiu/Hive-JSON-Serde
Related
I am having issues reading a .dat file into a dataframe. I think the issue is with the delimiter. I have included a screen shot of what the data in the file looks like below. My best guess is that it is tab delimited between columns and then new-line delimited between rows. I have tried reading in the data with the following commands:
df = CSV.File("FORCECHAIN00046.dat"; header=false) |> DataFrame!
df = CSV.File("FORCECHAIN00046.dat"; header=false, delim = ' ') |> DataFrame!
My result either way is just a DataFrame with only one column including all the data frome each column concatenated into one string. I tried to even specify the types with the following code:
df = CSV.File("FORCECHAIN00046.dat"; types=[Float64,Float64,Float64,Float64,
Float64,Float64,Float64,Float64,Float64,Float64,Float64,Float64]) |> DataFrame!
And I received an the following error:
┌ Warning: 2; something went wrong trying to determine row positions for multithreading; it'd be very helpful if you could open an issue at https://github.com/JuliaData/CS
V.jl/issues so package authors can investigate
I can work around this by uploading it into google sheets and then downloading a csv, but I would like to find a way to make the original .dat file work.
Part of the issue here is that .dat is not a proper file format—it's just something that seems to be written out in a somewhat human-readable format with columns of numbers separated by variable numbers of spaces so that the numbers line up when you look at them in an editor. Google Sheets has a lot of clever tricks built in to "do what you want" for all kinds of ill-defined data files, so I'm not too surprised that it manages to parse this. The CSV package on the other hand supports using a single character as a delimiter or even a multi-character string, but not a variable number of spaces like this.
Possible solutions:
if the files aren't too big, you could easily roll your own parser that splits each line and then builds a matrix
you can also pre-process the file turning multiple spaces into single spaces
That's probably the easiest way to do this and here's some Julia code (untested since you didn't provide test data) that will open your file and convert it to a more reasonable format:
function dat2csv(dat_path::AbstractString, csv_path::AbstractString)
open(csv_path, write=true) do io
for line in eachline(dat_path)
join(io, split(line), ',')
println(io)
end
end
return csv_path
end
function dat2csv(dat_path::AbstractString)
base, ext = splitext(dat_path)
ext == ".dat" ||
throw(ArgumentError("file name doesn't end with `.dat`"))
return dat2csv(dat_path, "$base.csv")
end
You would call this function as dat2csv("FORCECHAIN00046.dat") and it would create the file FORCECHAIN00046.csv, which would be a proper CSV file using commas as delimiters. That won't work well if the files contain any values with commas in them, but it looks like they are just numbers, in which case it should be fine. So you can use this function to convert the files to proper CSV and then load that file with the CSV package.
A little explanation of the code:
the two-argument dat2csv method opens csv_path for writing and then calls eachline on dat_path to read one line form it at a time
eachline strips any trailing newline from each line, so each line will be bunch of numbers separated by whitespace with some leading and/or trailing whitespace
split(line) does the default splitting of line which splits it on whitespace, dropping any empty values—this leaves just the non-whitespace entries as strings in an array
join(io, split(line), ',') joins the strings in the array together, separated by the , character and writes that to the io write handle for csv_path
println(io) writes a newline after that—otherwise everything would just end up on a single very long line
the one-argument dat2csv method calls splitext to split the file name into a base name and an extension, checking that the extension is the expected .dat and calling the two-argument version with the .dat replaced by .csv
Try using the readdlm function in DelimitedFiles library, and convert to DataFrame afterwards:
using DelimitedFiles, DataFrames
df = DataFrame(readdlm("FORCECHAIN00046.dat"), :auto)
I am using a simple program to read CSV file, somehow I noticed when I created a CSV using EXCEL or windows based computer go library fails to read it. even when I use cat command it only shows me last line on the terminal. It always results in this error extraneous " in field.
I researched somewhat than I found it is somewhat related to carriage return differences between OS.
But I really want to ask how to make a generic csv reader. I tried reading the same csv using pandas and it was reading successfully. But i am not been able to achieve this using my Go code.
Also screen shot of correct csv Is here
Your file clearly shows that you've got an extra quote at the end of the content. While programs like pandas may be fine with that, I assume it's not valid csv so go does return an error.
Quick example of what's wrong with your data: https://play.golang.org/p/KBikSc1nzD
Update: After your update and a little bit of searching, I have to apoligize, the carriage return does matter and seems to be tha main culprit here, Go seems to be ok handling the \r\n windows variant but not the \r one. In that case what you can do is wrap the bytes.Reader into a custom reader that replaces the \r byte with the \n byte.
Here's an example: https://play.golang.org/p/vNjzwAHmtg
Please note, that the example is just that, an example, it's not handling all the possible cases where \r might be a legit byte.
I get data from a CSV format daily.
Example data looks like:
Emp_ID emp_leave_id EMP_LEAVE_reason Emp_LEAVE_Status Emp_lev_apprv_cnt
E121 E121- 21 Head ache, fever, stomach-ache Approved 16
E139 E139_ 5 Attending a marraige of my cousin Approved 03
Here you can see that emp_leave_id and EMP_LEAVE_reason column data is shifted/scattered into the next columns.
So the problem by using tFileInputDelimited and various reading patterns I couldn't load data correctly into my target database. Mainly I'm not able to read the data correctly with that component in Talend.
Is there a way that I can properly parse this CSV to get my data in the format that I want?
This is probably a TSV file. Not sure about Talend, but uniVocity can parse these files for you:
TsvDataStoreConfiguration tsv = new TsvDataStoreConfiguration("my_TSV_datastore");
tsv.setLimitOfRowsLoadedInMemory(10000);
tsv.addEntities("/some/dir/with/your_files", "ISO-8859-1"); //all files in the given directory path will accessible entities.
JdbcDataStoreConfiguration database = new JdbcDataStoreConfiguration("my_Database", myDataSource);
database.setLimitOfRowsLoadedInMemory(10000);
Univocity.registerEngine(new EngineConfiguration("My_ETL_Engine", tsv, database));
DataIntegrationEngine engine = Univocity.getEngine("My_ETL_Engine");
DataStoreMapping dataStoreMapping = engine.map("my_TSV_datastore", "my_Database");
EntityMapping entityMapping = dataStoreMapping.map("your_TSV_filename", "some_database_table");
entityMapping.identity().associate("Emp_ID", "emp_leave_id").toGeneratedId("pk_leave"); //assumes your database does not keep the original ids.
entityMapping.value().copy("EMP_LEAVE_reason", "Emp_LEAVE_Status").to("reason", "status"); //just copies whatever you need
engine.executeCycle(); //executes the mapping.
Do not use a CSV parser to parse TSV inputs. It won't handle escape sequences properly (such as \t inside the value, you will get the escape sequence instead of a tab character), and will surely break if your value has a quote in it (a CSV parser will try to find the closing quote character and will keep reading chars until it finds another quote)
Disclosure: I am the author of this library. It's open-source and free (Apache V2.0 license).
I am uploading data from a a big .csv file into Cassandra using copy in cqlsh.
I am using cassandra 1.2 and CQL 3.0.
However since " is part of my data I have to use some other character for uploading my data, I need to use any extended ASCII characters. I tried various approaches but fails.
The following works, but need to use an extended ascii characters for my purpose..
copy (<columnnames>) from <filename> where deleimiter='|' and quote = '"';
copy (<columnnames>) from <filename> where deleimiter='|' and quote = '~';
When I give quote='ß', I get the error below:
:"quotechar" must be an 1-character string
Pls advice on how I can use an extended ASCII character for quote parameter..
Thanks in advance
A note on the COPY documentation page suggests that for bulk loading (like in your case), the json2sstable utility should be used. You can then load the sstables to your cluster using sstableloader. So I suggest that you write a script/program to convert your CSV to JSON and use these tools for your big CSV. JSON will not have any problem handling all characters from ASCII table.
I had a similar problem, and inspected the source code of cqlsh (it's a python script). In my case, I was generating the csv with python, so it was a matter of finding the right python csv parameters.
Here's the key information from cqlsh:
csv_dialect_defaults = dict(delimiter=',', doublequote=False,
escapechar='\\', quotechar='"')
So if you are lucky enough to generate your .csv file from python, it's just a matter of using the csv module with:
writer = csv.writer(open("output.csv", 'w'), **csv_dialect_defaults)
Hope this helps, even if you are not using python.
I'm trying to write a csv file with the delimiter ctrl+a. I'm going to have to eventually write the file to hadoop and I'm unable to use a standard delimiter.
Currently I'm trying this:
writer = csv.writer(f, delimiter = "\u0001")
for item in aList:
writer.writerow(item)
f.close()
However, the outputted excel file doesn't appear to be written correctly...
Some rows are condensed into one block, while others will have one field in the first and then the rest condensed into the second block, etc.
Is the error where I'm setting up the writer object, or am I just not familiar with separating files this way?
You can try using the nonprinting "group separator" character, which can be represented in python code as '\035'
see http://www.asciitable.com/index/asciifull.gif for some other nonprinting characters if you need more.
It may be helpful to include more context about why you want to use nonstandard delimiter. And whether Excel parsing of the file is necessary, or just a quick check to see if the file might be parsed properly by the target system, Hadoop.