BigQuery is a fully managed, petabyte-scale analytics data warehouse that enables businesses to analyze all their data very quickly. It is a serverless platform, so you don’t need to worry about managing any infrastructure. You can simply load your data into BigQuery and start querying it using SQL. BigQuery is also very cost-effective, as you only pay for the storage and querying that you use.
## Dataset Schema - blocks
- **number**: The block number
- **hash**: Hash of the block
- **parent_hash**: Hash of the parent of the block
- **nonce**: Nonce that satisfies the difficulty target
- **sha3_uncles**: Combined has of all uncles for a given parent
- **logs_bloom**: Data structure containing event logs
- **transactions_root**: Root hash of the transactions in the payload
- **state_root**: Root hash of the state object
- **receipts_root**: hash of the transaction receipts tree
- **miner**: The address of the beneficiary to whom the mining rewards were given
- **difficulty**: Integer of the difficulty for this block
- **total_difficulty**: Total difficulty of the chain until this block
- **size**: The size of this block in bytes
- **extra_data**: Arbitrary additional data as raw bytes
- **gas_limit**: The maximum gas allowed in this block
- **gas_used**: The total used gas by all transactions in this block
- **timestamp**: The timestamp for when the block was collated
- **transaction_count**: The number of transactions in the bloc
blocks_df.info()
RangeIndex: 16967424 entries, 0 to 16967423
Data columns (total 4 columns):
Column Dtype
--- ------ -----
0 timestamp datetime64[ns, UTC]
1 transaction_count Int64
2 miner object
3 size Int64
dtypes: Int64(2), datetime64[ns, UTC](1), object(1)
memory usage: 550.2+ MB
CPU times: user 11.4 ms, sys: 304 µs, total: 11.7 ms
Wall time: 36.1 ms
Part A. Time Analysis (25%)
Create a bar plot showing the number of transactions occurring every month between the start and end of the dataset.
Total Transactions per Year-Month
Part B. Top Ten Most Popular Services (25%)
Evaluate the top 10 smart contracts by total Ether received. You will need to join address field in the contracts dataset to the to_address in the transactions dataset to determine how much ether a contract has received.
## Dataset Schema - contracts
- **address**: Address of the contract
- **bytecode**: Code for Ethereum Contract
- **function_sighashes**: Function signature hashes of a contract
- **is_erc20**: Whether this contract is an ERC20 contract
- **is_erc721**: Whether this contract is an ERC721 contract
- **block_number**: Block number where this contract was created
address
0xd4039ecc40aeda0582036437cf3ec02845da4c13 5280000000000000000000.000000
0x8a46b5dd6e1aa09619245ff386cff5a624cddddb 4500900000000000000000.000000000
0xe9603c91ef4334450671b1e4a6cad611ba20bbf1 3976237731316744024643.000000
0xb8901acb165ed027e32754e0ffe830802919727f 1709610360292951025469.000000
0x89e7a245d5267ecd5bf4ca4c1d9d4d5a14bbd130 1600000000000000000000.000000
0x30b561304a4cd1f9941ab99be06d53a6cb341167 818000000000000000000.000000000
0x89cd1b96aa6dfb50d2b70ba29c026793602423ca 200000000000000000000.000000000
0x54edc8496f1e97fe7af2928e5b258cdda35c6ca3 138874124753428342453.0000000
0x13dc57a190808e3bde97a625093d66212d101fc4 79250898615375547000.00000000
0xdbd324b73f6f85bf9013b75c442021303b635ff9 67679600000000000000.00000000
top_10
Part C. Top Ten Most Active Miners (10%)
Evaluate the top 10 miners by the size of the blocks mined. This is simpler as it does not require a join. You will first have to aggregate blocks to see how much each miner has been involved in. You will want to aggregate size for addresses in the miner field. This will be similar to the wordcount that we saw in part-1 and part -2. You can add each value from the reducer to a list and then sort the list to obtain the most active miners.
Miner Total_block_size
0xea674fdde714fd979de3edf0f56aa9716b898ec8 130337685085
0x5a0b54d5dc17e0aadc383d2db43b0a0d3e029c4c 65704646587
0x829bd824b016326a401d083b33d092293333a830 63253546382
0xdafea492d9c6733ae3d56b7ed1adb60692c98bc5 35209001625
0x690b9a9e9aa1c9db991c7721a92d351db4fac990 28985235316
0x52bc44d5378309ee2abf1539bf71de1b7d7be3b5 27120033449
0x95222290dd7278aa3ddd389cc1e1d165cc4bafe5 21829279186
0x1ad91ee08f21be3de0ba2ba6918e714da6b45836 21232642110
0x00192fb10df37c9fb26829eb2cc623cd1bf599e8 13184407748
0x1f9090aae28b8a3dceadf281b0f12828e676c326 12959806717
0x388c818ca8b9251b393131c08a736a67ccb19297 12214326789
0x04668ec2f57cc15c381b461b9fedab5d451c8f7f 10071546636
0x7f101fe45e6649a6fb8f3f8b43ed03d353f2b90c 9734692078
0xb2930b35844a230f00e51431acae96fe543a0347 9176722960
0x3ecef08d0e2dad803847e052249bb4f8bff2d5bb 8279469687
0x99c85bb64564d9ef9a99621301f22c9993cb89e3 6581350291
0xb7e390864a90b7b923c9f9310c6f98aafe43f707 5846330629
0x4675c7e5baafbffbca748158becba61ef3b0a263 5798062347
0xd224ca0c819e8e97ba0136b3b95ceff503b79f53 4699309633
0xb3b7874f13387d44a3398d298b075b7a3505d8d4 4408521354
0xf2f5c73fa04406b1995e397b55c24ab1f3ea726c 4293646940
0xbaf6dc2e647aeb6f510f9e318856a1bcd66c5e19 4203155532
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0x8fa646bd64055fdfd8dea8fb739d86584e3ab59d 12742958
0xcd024414b9fd0c702df325ecc762f0bf8b32f46a 12669539
0xa50db79f131f7e093aaa862b5b7d404fb7fecafb 12656917
0xc17e602ac1c8f4ad9e4b2dfaa3442e393893ae17 12597104
0x82d9730e487dccd1106ebd9ffa5f1200950e7002 12517442
0x9bd73b0535d0e02aefc66c9ddbbf9ff35d156350 12349829
0x751bc4cd7e77033fbdb9206ff306549d6dd017f8 12298110
0x904485256c5424eecd8cf83f1584a82052ad2a34 12275640
0x4038c8bcddc8aa5910b8cde9c1bfe7379aaeae5e 12171023
0x7224e2887d20c4286f928d43f2c2aeb94bbcd500 12147443
0xd725cf73831235a459e4dde279dd4af9002f4d5c 12126930
0x4d17676309cb16fa991e6ae43181d08203b781f8 12078929
0x6e94a05021d369ff5de639dca57a7d33d1d7e446 12058236
0xb35c1055aae02da8497e9dd866e27c86be16cfef 12057793
0x0f482c40b47d3f448d69383401ed82149f8670d8 12043451
0x03d749c354e9024fc6e0041ea964e4d219d7a4b9 11966059
0xa2feb87cb3ca94ea27f45ca30069f15279e143f4 11825450
0x5caf7c1b096cf684b09ece3d3a142db0d46fc58e 11823833
Conclusion
In conclusion, we have analyzed the Ethereum blockchain dataset and presented the results of three analyses. The time analysis showed the monthly trend of the number of transactions and average 9 transaction value. The top ten most popular services analysis showed the smart contracts that received the most Ether. The top ten most active miners analysis showed the miners that mined the most blocks by size. These analyses can provide insights into the usage and performance of the Ethereum network.