I created a table in my Azure Data Explorer with the following command:
.create table MyLogs ( Level:string, Timestamp:datetime, UserId:string, TraceId:string, Message:string, ProcessId:int32 )
I then created my Storage Account --> Container and i then uploaded a simple txt file with the following content
Level Timestamp UserId TraceId Message ProcessId
I then generated a SAS for the container holding that txt file and used in into the query section of my Azure Data Explorer like the following:
.ingest into table MyLogs (
h'...sas for my txt file ...')
Now, when i read the table i see something like this
Level TimeStamp UserId TraceID MEssage ProcessId
Level Timestamp UserId TraceId Message ProcessId
So it basically put all the content into the first column.
I was expecting some automatic splitting. I tried with tab, spaces, commas and many other separators.
I tried to configure an injection mapping with csv format but had no luck.
For what I understood, each new line in the txt is a new row in the table. But how to split the same line with some specific separator?
I read many pages of documentation but had no luck
You can specify any of the formats that you want to try using the format argument, see the list of formats and the ingestion command syntax example that specify the format here
In addition, you can use the "one click ingestion" from the web interface.
This should work (I have done it before with Python SDK)
.create table MyLogs ingestion csv mapping 'MyLogs_CSV_Mapping' ```
[
{"Name":"Level","datatype":"datetime","Ordinal":0},
{"Name":"Timestamp","datatype":"datetime","Ordinal":1},
{"Name":"UserId","datatype":"string","Ordinal":2},
{"Name":"TraceId","datatype":"string","Ordinal":3},
{"Name":"Message","datatype":"string","Ordinal":4},
{"Name":"ProcessId","datatype":"long","Ordinal":5}
]```
https://learn.microsoft.com/de-de/azure/data-explorer/kusto/management/data-ingestion/ingest-from-storage
.ingest into table MyLogs SourceDataLocator with (
format="csv",
ingestionMappingReference = "MyLogs_CSV_Mapping"
)
Hopefully this will help a bit :)
Related
I am new to databricks (pyspark), I have few queries regarding pyspark syntax:
Do we need to follow any specific order when using options in readStream and writeStream. For example:-
(dataframe.readStream
.format("cloudFile)
.option("cloudFiles.format": "avro")
.option("multiline", True)
.schema(schema)
.load(path))
Delta table creation w/ both tableName and location option, is that right?? If I use both only I can see the files like .parquet, _delta log, checkpoint in the specified path and if I use tableName only I can see the table in hive meta store/spark catalog.bronze of SQL editor in databricks
The syntax i use, is it ok to use both .tableName() and .location() option
(DeltaTable.createIfNotExists(spark)
.tableName("%s.%s_%s" % (layer, domain, deltaTable))
.addColumn("x", "INTEGER")
.location(path)
.execute())
1st question: Do we need to follow any specific order when using options in readStream and writeStream.
Answer: No order required you can use different options like format, option, schema, etc in any order
2nd Question: Delta table creation w/ both tableName and location option, is that right?? If I use both only I can see the files like .parquet, _delta log, checkpoint in the specified path and if I use tableName only I can see the table in hive meta store/spark catalog.bronze of SQL editor in databricks
Answer: If you specify the location explicitly, it is external table (this table is created under specified location and once table alone is deleted the data still persists under data store location like mounted ADLS) and if you don't specify location it is managed table (create under default location and this table can be deleted once the table is deleted)
And to the question in the heading/top of the question about rescued data column:
Answer: Even though we use option to see rescued data, we need to select that rescued data column so that we can see it in the resultant dataframe. If we don't select it in: df.select(), then we can't see it in the result.
Please correct me if I am wrong.
I have an input to my stream analytics job as a CSV string such as follows:
jon,41,111 treadmill lane,07831231123,aa,bb,123...etc.
I'd like to sort this data into columns of an SQL table with column headings:
name,age,address,phone,result1,result2,result3...etc.
I've tried using SQL split functions but none I've tried seem to be compatible with Azure stream analytics job query. Could anyone provide any assistance as to how I can split my string into the appropriate tables? Many thanks.
If your events are coming in with a CSV format, you don't have to do anything in your query to work with it. The trick is to set the correct serialisation for your input. When you create your IoT Hub input, set the serialisation to CSV:
This will work if your CSV message has the headers included in the message:
name,age,address,phone,result1,result2,result3
jon,41,111 treadmill lane,07831231123,aa,bb,123
It will show up in the input preview like so:
When the headers are present, you can use them in your queries.
SELECT
name,
age
INTO
target
FROM
[csv-input]
I'm trying to solve following scenario in Azure Data Factory:
I have a large number of folders in Azure Blob Storage. Each folder contains varying number of files in parquet format. Folder name contains the date when data contained in the folder was generated, something like this: DATE=2021-01-01. I need to filter the files and save them into another container in delimited format and each file should have the date indicated in source folder name in it's file name.
So when my input looks something like this...
DATE=2021-01-01/
data-file-001.parquet
data-file-002.parquet
data-file-003.parquet
DATE=2021-01-02/
data-file-001.parquet
data-file-002.parquet
...my output should look something like this:
output-data/
data_2021-01-01_1.csv
data_2021-01-01_2.csv
data_2021-01-01_3.csv
data_2021-01-02_1.csv
data_2021-01-02_2.csv
Reading files from subfolders and filtering them and saving them is easy. Problems start when I'm trying to set output dataset file name dynamically. I can get the folder names using Get Metadata activity and then I can use ForEach activity to set them into variables. However, I can't figure out how to use this variable in filtering data flow sinks dataset.
Update:
My Get Metadata1 activity, set the container input as:
Set the container input as follows:
My debug info is as follows:
I think I've found the solution. I'm using csv files for example.
My input looks something like this
container:input
2021-01-01/
data-file-001.csv
data-file-002.csv
data-file-003.csv
2021-01-02/
data-file-001.csv
data-file-002.csv
My debug result is as follows:
Using Get Metadata1 activity to get the folder list and then using ForEach1 activity to iterate this list.
Inside the ForEach1 activity, we now using data flow to move data.
Set the source dataset to the container and declare a parameter FolderName.
Then add dynamic content #dataset().FolderName to the source dataser.
Back to the ForEach1 activity, we can add dynamic content #item().name to parameter FolderName.
Key in File_Name to the tab. It will store the file name as a column eg. /2021-01-01/data-file-001.csv.
Then we can process this column to get the file name we want via DerivedColumn1.
Addd expression concat('data_',substring(File_Name,2,10),'_',split(File_Name,'-')[5]).
In the Settings of sink, we can select Name file as column data and File_Name.
That's all.
It's seem ADF v2 does not support writing data to TEXT file (.TXT).
After select File System
But don't see TextFormat at the next screen
So do we any method to write data to TEXT file ?
Thanks,
Thai
Data Factory only support these 6 file formats:
Please see: Supported file formats and compression codecs in Azure Data Factory.
If we want to write data to a txt file, the only format we can using is Delimited text, when the pipeline finished, you will get a txt file.
Reference: Delimited text: Follow this article when you want to parse the delimited text files or write the data into delimited text format.
For example, I create a pipeline to copy data from Azure SQL to Blob, choose DelimitedText format as Sink dataset:
The txt file I get in Blob Storeage:
Hope this helps
I think what you are looking for is DelimitedText dataset. You can specify extension as part of the file name
I have lots of json files in my Azure Data Lake account. They are organized as: Archive -> Folder 1 -> JSON Files.
What I want to do is extract a particular field: timestamp from each json and then then just put it in a csv file.
My issue is:
I started with this script:
CREATE ASSEMBLY IF NOT EXISTS [Newtonsoft.Json] FROM "correct_path/Assemblies/JSON/Newtonsoft.Json.dll";
CREATE ASSEMBLY IF NOT EXISTS [Microsoft.Analytics.Samples.Formats] FROM "correct_path/Assemblies/JSON/Microsoft.Analytics.Samples.Formats.dll";
REFERENCE ASSEMBLY [Newtonsoft.Json];
REFERENCE ASSEMBLY [Microsoft.Analytics.Samples.Formats];
DECLARE #INPUT_FILE string = #"correct_path/Tracking_3e9.json";
//Extract the different properties from the Json file using a JsonExtractor
#json =
EXTRACT Partition string, Custom string
FROM #INPUT_FILE
USING new Microsoft.Analytics.Samples.Formats.Json.JsonExtractor();
OUTPUT #json
TO "correct_path/Output/simple.csv"
USING Outputters.Csv(quoting : false);
I get error:
E_STORE_USER_FILENOTFOUND: File not found or access denied
But I do have access to the file in the data explorer of the Azure Data Lake, so how can it be?
I don't want to run it for each file one by one. I just want to give it all the files in a folder (like Tracking*.json) or just a bunch of folders (like Folder*) and it should go through them and put the output for each file in a single row of the output csv.
Haven't found any tutorials on this.
Right now, I am reading the entire json, how to read just one field like time stamp which is a field within a particular field, like data : {timestamp:"xxx"}?
Thanks for your help.
1) Not sure why you're running into that error without more information - are you specifically missing the input file or is it the assemblies?
2) You can use a fileset to extract data from a set of files. Just use {} to denote the wildcard character in your input string, and then save that character in a new column. So for example, your input string could be #"correct_path/{day}/{hour}/{id}.json", and then your extract statement becomes:
EXTRACT
column1 string,
column2 string,
day int,
hour int,
id int
FROM #input
3) You'll have to read the entire JSON in your SELECT statement, but you can refine it down to only the rows you want in future rowsets. For example:
#refine=
SELECT timestamp FROM #json;
OUTPUT #refine
...
It sounds like some of your JSON data is nested however (like the timestamp field). You can find information on our GitHub (Using the JSON UDFs) and in this blog for how to read nested JSON data.
Hope this helps, and please let me know if you have additional questions!