How to compose a row key in BigTable?

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In https://cloud.google.com/bigtable/docs/schema-design it is clearly described how to choose the row key of a table. But I could not find any info on how to compose this row key. Where and by what means it is composed?

I'm not sure I understand your question, but I'll try to shed some light on row keys in general. Unlike SQL tables, you don't need to create a primary key column, Bigtable tables already have a concept of a primary key built in. You just need to decide what you want to store in it. Implementation wise, Bigtable doesn't try to interpret the keys and treats them as a byte array.

The values on the other hand, need at least one column family created before inserting data. You can create column families using the cbt command line tool. You can find the instructions how to install it here: https://cloud.google.com/bigtable/docs/go/cbt-overview And general information about managing tables here: https://cloud.google.com/bigtable/docs/managing-tables.

Designing your schema | Cloud Bigtable Documentation, rowKey := "phone#4c410523#20190501" if err := tbl.Apply(ctx, rowKey, mut); err != nil { return fmt. Fprintf(w, "Successfully wrote row: %s\n", rowKey) return nil To get the best performance out of Cloud Bigtable, it's essential to think carefully about how you compose your row key. That's because the most efficient Cloud Bigtable queries use the row key, a row key prefix, or a row range to retrieve the data. Other types of queries trigger a full table scan, which is much less efficient.

Row keys are simple byte strings that are sorted to create a full table. Rows can be composed of multiple parts concatenated together, considering what parts belong to the row and in what order, as that corresponds to how much content will go into the row (There is a limit of 100MB per row) and how efficient it will be to scan contiguous rows.

The Cloud Bigtable documentation for schema design is here: https://cloud.google.com/bigtable/docs/schema-design

The same concepts apply for HBase and similar databases: https://mapr.com/blog/guidelines-hbase-schema-design/

Writing data | Cloud Bigtable Documentation, When you create a table, you can choose row keys to pre-split the table. For example, you might designate specific  Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, enabling you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key. Cloud Bigtable is ideal for storing very large amounts of single-keyed data with very low latency.

Here's a Python code sample that creates a sample row key and adds it to a list of keys returned from a CBT table:

SampleRowKey = namedtuple("SampleRowKey", "row_key offset_bytes")
keys.insert(0, SampleRowKey(b'', 0))

Hope this helps.

Cloud Bigtable writes | Cloud Bigtable Documentation, Note: Two of the row keys in this example are identical, which indicates that the table is storing two versions of the data for that row key. Row keys must always be  Cloud Bigtable eventually splits your table on different row keys, based on how much data is in the table and how frequently each row is accessed. To pre-split a table based on the row key, use the

Managing tables | Cloud Bigtable Documentation, In this new table, we can start to insert new data using our changed row key design. If all processes writing into the legacy table have been  Cloud Bigtable stores data in tables, which contain rows. Each row is identified by a row key . Data in a row is organized into column families , which are groups of columns.

Schema Design for Time Series Data, Performance wise, this simple design was creating a massive By choosing the correct row key template, you can avoid a painful data  This page describes how to use BigQuery to query data stored in Cloud Bigtable. Cloud Bigtable is Google's sparsely populated NoSQL database which can scale to billions of rows, thousands of columns, and petabytes of data.

How to update row keys in Google Big Table, or multi-row transactions. This makes it unsuitable for a wide range of applications, especially online transaction processing. Fourth, it's designed to store key/value pairs. Unlike most map implementations, in Hbase/BigTable the key/value pairs are kept in strict alphabetical order. That is to say that the row for the key "aaaaa" should be right next to the row with

Comments
  • Thanks for the response, but I still don't understand why in that article they say that we need "to think carefully about how you compose your row key". What do they mean by "compose your row key", how can I control this process?
  • Row keys are usually "composed" of several things, for example a user id follow by delimiter followed by a timestamp (so something like user1234~1506100147). You control this process by specifying a row key each time you insert some data into a Bigtable table. It's sort of like a regular hash table or dictionary - you decide the row key when you insert something and pull things out later using the same key. Example code might help with this. cloud.google.com/bigtable/docs/samples-python-hello cloud.google.com/bigtable/docs/samples-java-hello
  • You need to design your row keys carefully to avoid hotspotting.