# docs/source/working-notes/troyraen/performance-figures/figures/allwise/README.md ## AllWISE BigQuery cross match [billing#billing]() ```python from matplotlib import pyplot import figures as figs query = { 'survey': 'ztf', 'testid': False, 'date': '20210923', # 'limit': 100, 'columns': [ 'kafka_timestamp__alerts', 'publish_time__alerts', 'publish_time__BigQuery', 'publish_time__alert_avros', # 'publish_time__AllWISE', # 'publish_time__alerts_pure', 'publish_time__exgalac_trans_cf', 'publish_time__SuperNNova', ] } savefig_dir = 'figures/20210923' mplot = figs.MetadataPlotter(query=query, savefig_dir=savefig_dir) # mplot = figs.MetadataPlotter(df=mplot.df, query=query, savefig_dir=savefig_dir) # plot processing times with marginal histograms cols = ['alerts', 'BigQuery', 'alert_avros', 'exgalac_trans_cf', 'SuperNNova'] clip_first = 0 tref = 'trigger' # clip_first = 90 c = ['AllWISE'] # t0 = ('publish_time__alerts', 'trigger') # title = "Cross match with AllWISE BigQuery public dataset; Cloud Run" for tref in ['kafka', 'trigger']: plot_proct() def plot_proct(): fig = plt.figure() gs = fig.add_gridspec(2, 2, width_ratios=(7, 1.3), height_ratios=(2, 7), left=0.1, right=0.9, bottom=0.1, top=0.9, wspace=0.05, hspace=0.05) ax = fig.add_subplot(gs[1, 0]) marg_ax = { 'x': fig.add_subplot(gs[0, 0], sharex=ax), 'y': fig.add_subplot(gs[1, 1], sharey=ax), } mplot.plot_proc_time(c, ax, tref=tref, clip_first=clip_first, marg_ax=marg_ax) fig.autofmt_xdate() fig.suptitle(f"{c.split('__')[-1]}") # fig.suptitle(title) mplot._save_or_show(f'{c}-{tref}') if mplot.savefig_dir is not None: plt.close(fig) ``` ### Billing GCPbilling-bigquery-20210926.png BigQuery billing after the first night (9/26), *before* 9/27 topic started. The first night had errors that caused a backlog of ~20,000 alerts lasting a few hours. Sept 27 should be the first normal "night".