Google Storage – Anodot

This article describes how to create the Google Storage data source and includes:

Creating a Google Storage Data Source
Creating and Editing a Stream Query
Recommended Practices

Creating a Google Storage Data Source

In the Navigation Panel, go to Integrations > Catalog.
Use the Search box OR click the Storage filter to locate the data source
Click Start on the Google Storage tile. The Google Storage dialog box is displayed.
Either enter your Google Service Account, see Google Service Accounts, or click Sign in with Google and follow the on screen instructions. The Stream Query Google Cloud Storage window is displayed.
In the Files to Collect section:
In the Files Path field enter a path relative to the data source.
[Optional] You can further restrict access to the source by continuing the path to a specific folder within the bucket.

Choose a File Name Date Pattern and collection interval:

Filename Timestamp Pattern	Example	Supported Intervals
yyyyMMdd	test_20180715_daily.csv.gz	Daily
yyyyMMddHH	test_2018071503_hourly.csv.gz test_2018071504_hourly.csv.gz test_2018071505_hourly.csv.gz	Daily, hourly ^[1]
yyyyMMddHHmm	test_201807150305_5min.csv.gz test_201807150310_5min.csv.gz test_201807150300_15min.csv.gz test_201807150315_15min.csv.gz test_201807150330_15min.csv.gz test_201807150345_15min.csv.gz	Daily, hourly, 15 minutes, 5 minutes ^[2]

^{[1] If daily - the most recent file will be used
[2] For daily, hourly, 15 minutes, 5 minutes, 1 minute - the most recent file will be used}

In the File name prefix field, enter the prefix (e.g. test_ ).
In the File name suffix field, enter suffix and extension (e.g. _demo.csv.gz).

Notes:
- In each of the Timestamp/Prefix/Suffix fields enter the specified data only.
- Files may be compressed [.gz].
- If you get an error message, fix the error in the bucket or files, and click RETRY to re-fetch the files.
To preview the file, click. [Optional]
To change the Parsing and Import Settings, click.
See CSV - Parsing and Importing Settings.

Creating and Editing a Stream Query

If you just created a Google Storage data source, skip to step 3.

In the Sources page (accessed by clicking Integrations > Sources in the Navigation Panel), filter the list of streams to find the source for which you want to create a stream query.
Note: If the Streams panel is empty, no stream queries exist for that source.
Hover over the Google Storage data source, and click + New Stream. The Stream Query page is displayed.
Note: To edit a stream, click the More icon > Edit.
In the Measures & Dimensions section, click the edit icon.

To add an item, drag from the Available Fields repository to the relevant Measure or Dimension panel. At least one dimension and one measure [a numerical value] are required.
Note Use Search if an item is not displayed.
To clear an item, click the X icon on the item.
Choose a time format from the drop-down menu.
Choose a time zone.

4. Click X to accept the edits and return to the Stream Query window.
5. In the Schedule File Collection panel, click the Pen icon.

From the Collect files every menu, set the collection interval [daily/ hourly/ 15 min/ 5 min].
Note: The timestamp at the start of the source file name indicates the the period of the hourly or daily data. Each row in a file will increase incrementally, either hourly or daily, accordingly.
A File Time Zone for Anodot to know how to relate to the internal timestamp.
An Ignore files older than time span.
Note: "Older than" refers to back filing of historical data and does not affect ongoing collection.
A Lagging files policy to set the number of intervals to waits for lagging files.

Note: The system behavior in general is to keep the data ordered, and create as minimal gaps as possible. Therefore, the heuristics are the following:

1. While there is no new data, meaning no new files, the system will retry to collect from the last file collected. In this case, the lag policy parameter does not affect anything.
2. When there is a gap followed by new files, the Lagging files parameter is used to state "how many intervals the system should wait before processing the new files". So that the file hold processing is not too long, due to missing files that may never or are too-long in arriving.

Example
File 2018032806_test.csv was collected OK - Anodot has collected the data up to 2018/03/28 at 06:59
The files for 07,08, 09 have not arrived to the relevant folder.
The file for 10, called 2018032810_test.csv arrived at 11:15 - therefore there is a gap.

The Lagging files parameter determines the processing of the 10 o'clock file:

Lag policy = 0 --> The 10 file will be processed upon arrival, and a gap in the previous hours is created.

Lag policy = 1 --> The 10 file will not be processed yet, it will wait to 12:15 and then be processed. [If during the waiting time, older files arrive, they will be processed before.]

Lag policy = 2 --> The 10 file will not be processed yet, it will wait to 13:15 and then be processed. [If during the waiting time, older files arrive, they will be processed before.]

6. Click X to accept the scheduling settings.

7. Click NEXT. The Stream Table is displayed.

Recommended Practices

Before uploading a data set file to a Google Storage source type:

Prepare the file in a test folder; check that the file format meets the Google Storage data source file parameters.
Records within files must be sorted chronologically.
Note: Files smaller than 16MB are automatically sorted by timestamp by Anodot.
Move the file to the production folder only after you have verified that the file is complete.

Note:

If the file timestamp is epoch seconds or epoch milliseconds, don't define a timezone - it will be treated as an error.
The file must be formatted using UTF-8 or ASCII character sets.
A Google Storage bucket can be accessed from one Anodot account.

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Creating a Google Storage Data Source

Creating and Editing a Stream Query

Recommended Practices