Google Bigquery
Introduction
Blockchain Analytics offers indexed blockchain data made available through BigQuery for easy analysis through SQL.
Blockchain Analytics offers you access to reliable data without the overhead of operating nodes or developing and maintaining an indexer. You can now query the full history of blocks, transactions, logs and receipts for Cronos.
By leveraging datasets in BigQuery, you can access blockchain data as easily as your internal data. By joining chain data with application data, you can get a complete picture of your users and your business.
How are these datasets different from the existing public dataset?
Like the existing public blockchain datasets, customers are not charged for storage of the data, only for querying the data based on BigQuery pricing.
Quickstart
Go to Cronos dataset and click on one of the samples.
You will get to the console and see the Cronos dataset on the left in the explorer
Please note BigQuery charges are based on the amount of data processed by your queries, so running the query may incur charges to your account. You can find the consumption estimate in the top right corner similar to the warning of "This query will process 65.73 MB when run."
If you see on the sample you should get the BigQuery SQL code to query: Which wallets had the most number of interactions with the Wrapped Cronos contract in the past 30 days?
Let's click the big
RUN
button. (To save costs, replace the existing query with the one below, using a "1 day" interval instead of "30 days" in the BigQuery console). To start developing your own BigQuery SQL code, we refer to the following syntax. For the Cronos data schema we refer to the Google Cloud Cronos schema.
We can now query the results in the results tab below, further explore by exporting the results or visualizing in another tool such as Google sheets or Looker.
Row | address | cronoscan_link | num_transactions |
---|---|---|---|
1 | 0x3270c9a4558774cc8f2a19708edc190366028b96 | https://cronoscan.com/address/0x3270c9a4558774cc8f2a19708edc190366028b96 | 1 |
2 | 0xbeaf1c7fed452be2dcfd2a8fe1fcd74b241acfc7 | https://cronoscan.com/address/0x693fb96fdda3c382fde7f43a622209c3dd028b98 | 1 |
3 | 0xddb162b31f562f1be0fa585d3ca6a55786e59af3 | https://cronoscan.com/address/0x6614d26064d762922c7bc7a00337713d5169ae7c | 1 |
Example queries
Latest indexed block
Row | First block | Newest block | Total number of blocks | |
---|---|---|---|---|
1 | 1 | 12134627 | 12134627 |
Daily transactions in the last 10 days
Row | date | num_transactions |
---|---|---|
1 | 2024-01-18 | 10250 |
2 | 2024-01-17 | 47747 |
3 | 2024-01-16 | 49717 |
4 | 2024-01-15 | 47099 |
5 | 2024-01-14 | 47051 |
6 | 2024-01-13 | 43926 |
7 | 2024-01-12 | 50448 |
8 | 2024-01-11 | 60904 |
9 | 2024-01-10 | 61774 |
10 | 2024-01-09 | 54521 |
11 | 2024-01-08 | 44194 |
View the blocks with largest CRO value transfer in the past hour
Row | block_hash | value_total |
1 | 0x7cac0bbf3909902a8670f962fbc9721391178850a2672d82b75c5a79b332a4f8 | 36836.840925000000000001 |
2 | 0xb53bd2c1a1d136e9b4dda4af47c488d278a0ee450adecd991cf13b187ce17a93 | 36729 |
3 | 0x28e0d8c31625ca43b565f1202b91e6cb20b709e25bea65185dcda7a3d176957d | 33359.85627 |
4 | 0xfe8e732779101854cfaeed2404f7b53d3b64879069b5d8e8372f64d1cfe4a47f | 22577.325273500000000015 |
5 | 0xd0b81821a57dc939dce80b29e9642f4a39e4bd2d346b5943a2532e69f191de57 | 22231.469422733370862931 |
Top 10 wallets by number of transactions in the last hour
Row | from_address | num_transactions |
---|---|---|
1 | 0x25aa97464f38a1506a16160bbc03cfc6dd863da3 | 211 |
2 | 0x227f6757289a86c13eee2e91c2e6eb03f2ed11a6 | 136 |
3 | 0x95d49a8a2d69b2a2de4a00655d05ee39f9c41108 | 134 |
4 | 0x15d190dd8a1ed39cf5b790e2ffed1f365e9c865b | 116 |
5 | 0xc9219731adfa70645be14cd5d30507266f2092c5 | 80 |
6 | 0x6614d26064d762922c7bc7a00337713d5169ae7c | 65 |
7 | 0x34cfa46732692ab062f0453036cd5a4f5b771473 | 59 |
8 | 0x693fb96fdda3c382fde7f43a622209c3dd028b98 | 50 |
9 | 0x71f0cdb17454ad7eeb7e26242292fe0e0189645a | 50 |
10 | 0x518a9d51ba8841046859a7722e75f92ffdadd0c4 | 37 |
All USDT activity in the past hour
Row | transaction_hash | from_address | to_address | usdt_transfer_amount |
1 | 0xa3b78f79dee6970f3abc763b52f24a6d46aeba3e2370943f8eb2d68ff00d788a | 0xc9219731adfa70645be14cd5d30507266f2092c5 | 0x539b85a6853e8740cd918009197c799d205787eb | 309.82 |
2 | 0xc2abd163669a703ee850e432ac7c1a744b63bb1ff8e9b4cdee3ec2d95768fc75 | 0xc9219731adfa70645be14cd5d30507266f2092c5 | 0xc041126c1d07b72ee0f366e1fca339b4fed537cb | 9.38 |
3 | 0x214cdef8263b4f8cc517d09673c126375c682b9b83d55c7ad889055c57533390 | 0xc9219731adfa70645be14cd5d30507266f2092c5 | 0xfca38e2882d8a549c660ccb17a8fe0463fab060e | 11.82 |
4 | 0x40e24cc93abc746aa7c96482144772421412b9a733210644bab6ff6290996a1e | 0xc9219731adfa70645be14cd5d30507266f2092c5 | 0x67b652172633b451a826aac6da7ed63693133fd2 | 11.26 |
5 | 0xb211dcb87ec8bbb115a4c6eae6c5a8861e04557b8b502e5a5858e70ae512183b | 0x539b85a6853e8740cd918009197c799d205787eb | 0x8995909dc0960fc9c75b6031d683124a4016825b | 309.82 |
6 | 0xff2bc840e8dd59bd1f680c6c0905aada50fb4149e298ac0b932e36fd6d44fa34 | 0xc447ea5dc46ec5f83cdfe17cf0ccf3730ea12036 | 0x515e9917819f11ab0b6b6e6cee3848a935003bf7 | 700.0 |
[DApp] Count the total number of unique transactions and users interaction with a specific smart contract on a given day
Row | total_transactions | unique_users | date |
1 | 288 | 131 | 2023-01-01 |
[DApp] Top 5 addresses with the highest number of transactions sent to the contract at a specific contract within the specified date range
Row | from_address | transaction_count |
1 | 0x8c0ec5772bd92d55edd1325d022ec07e54ae1b0e | 3515 |
2 | 0x849c34e2bcd65a861dfaefe415aafb2826c46b96 | 224 |
3 | 0xc9219731adfa70645be14cd5d30507266f2092c5 | 129 |
4 | 0xfe5b12a84019dcd8178a4c684885a8e685bef238 | 72 |
5 | 0x254b5fed7b453831e89e566a2e02678636e9f010 | 46 |
Last updated